library(dplyr)
library(lavaan)
library(DiagrammeR)
library(ggplot2)
library(tidyr)

# For saving SEM diagrams:
library(purrr)
library(DiagrammeRsvg)
library(rsvg)
library(png)
library(grid)
library(ggpubr)

Import data

combined=read.csv("data/monthly_averages/monthly_data_compiled_regions.csv",stringsAsFactors = F)
cnames=read.csv("analysis/column_names_region_monthly.csv", stringsAsFactors = F)
dsub=filter(combined, Year>=1995) %>% arrange(Region,Year,Month)
focaldata=dsub[,cnames$Datacolumn]
fvars=cnames$Shortname
colnames(focaldata)=fvars
regions=unique(focaldata$region)
regionorder=c("Far West","West","North","South")
focaldata=focaldata%>% 
  mutate(decyear=year+(month-1)/12)

focaldata = focaldata %>% 
  mutate(tzoop=hcope+clad+mysid+pcope+rotif_m,
         tzoop_e=hcope_e+clad_e+mysid_e+pcope_e+rotif_e,
         hzoop=hcope+clad+rotif_m,
         hzoop_e=hcope_e+clad_e+rotif_e,
         pzoop=mysid+pcope,
         pzoop_e=mysid_e+pcope_e,
         turbid=-secchi) 
fvars=c(fvars,"tzoop","tzoop_e",
        "hzoop","hzoop_e",
        "pzoop","pzoop_e","turbid")
cnames=rbind(cnames,data.frame(Longname=NA,Shortname=c("tzoop","tzoop_e",
                                                       "hzoop","hzoop_e",
                                                       "pzoop","pzoop_e","turbid"),
                               Diagramname=c("total zooplankton",
                                             "total zooplankton\nenergy",
                                             "herbivorous\nzooplankton",
                                             "herbivorous\nzooplankton\nenergy",
                                             "predatory\nzooplankton",
                                             "predatory\nzooplankton\nenergy",
                                             "turbidity"),
                               Datacolumn=NA,Log=c(rep("yes",6),"no"),
                               Color=c("black","black","#ED7D31","#ED7D31","#7030A0",
                                       "#7030A0","#4472C4")))

#focal variables
varnames=c("temp","flow","turbid","dophos","din","chla","hcope","clad","amphi_m","pcope","mysid","rotif_m","potam","corbic","sside","cent","sbass1_bsmt","marfish_bsmt","estfish_bsmt","tzoop","hzoop","pzoop")

#labels for lagged vars
cnameslag=cnames
cnameslag$Shortname=paste0(cnameslag$Shortname,"_1")
cnameslag$Diagramname=paste(cnameslag$Diagramname,"(t-1)")
cnameslag=rbind(cnames,cnameslag)

#labeld for growth rate
cnamesgr=cnames
cnamesgr$Shortname=paste0(cnamesgr$Shortname,"_gr")
cnamesgr$Diagramname=paste(cnamesgr$Diagramname,"(gr)")
cnameslag=rbind(cnameslag,cnamesgr)

source("analysis/myLavaanPlot.r")
source("analysis/semDiagramFunctions.r")

Data prep

Log transform, scale.
Within and across regions.
Create set with regional monthly means removed.

#log transform
logvars=fvars[cnames$Log=="yes"]
logtrans=function(x) {
  x2=x[which(!is.na(x))]
  if(any(x2==0)) {log(x+min(x2[which(x2>0)],na.rm=T))}
  else {log(x)}
}
focaldatalog = focaldata %>% 
  mutate(flow=flow-min(flow,na.rm=T)) %>%  #get rid of negative flow values
  mutate_at(logvars,logtrans) %>% 
  group_by(region) %>%
  mutate_at(logvars,list("gr"=function(x) {c(NA,diff(x))})) %>% 
  ungroup()

#scale data
fdr0=focaldatalog
tvars=fvars[-(1:3)]

#scaled within regions
fdr=fdr0 %>% 
  group_by(region) %>% 
  #scale
  mutate_at(tvars,scale) %>% 
  #lag
  mutate_at(tvars,list("1"=lag,"2"=function(x) {lag(x,2)})) %>% 
  ungroup() %>% 
  as.data.frame()

#scaled within regions, remove monthly means
fdr_ds=fdr %>% 
  group_by(region,month) %>%
  mutate_at(tvars,list("mm"=function(x) {mean(x,na.rm = T)})) %>% 
  mutate_at(tvars,function(x) {x-mean(x,na.rm = T)}) %>% 
  ungroup() %>% 
  #lag
  group_by(region) %>% 
  mutate_at(tvars,scale) %>% 
  mutate_at(tvars,list("1"=lag,"2"=function(x) {lag(x,2)})) %>% 
  ungroup() %>% 
  as.data.frame()

#scaled across regions
# fdr1=fdr0 %>% 
#   #scale
#   mutate_at(tvars,scale) %>% 
#   #lag
#   group_by(region) %>% 
#   mutate_at(tvars,list("1"=lag,"2"=function(x) {lag(x,2)})) %>% 
#   ungroup() %>% 
#   as.data.frame()

#scaled across regions, monthly means removed
# fdr1_ds=fdr1 %>% 
#   group_by(region,month) %>%
#   mutate_at(tvars,list("mm"=function(x) {mean(x,na.rm = T)})) %>% 
#   mutate_at(tvars,function(x) {x-mean(x,na.rm = T)}) %>% 
#   ungroup() %>% 
#   #lag
#   group_by(region) %>% 
#   mutate_at(tvars,list("1"=lag,"2"=function(x) {lag(x,2)})) %>% 
#   ungroup() %>% 
#   as.data.frame()

Data availability

Exclude individual zooplankton plankton groups from zooplankton model if rare (95% of values in a region are less than the across site mean, or more than 10% of values in a region are zeros).

sside and cent have no data in FW and W.

marfish and clams excluded if 95% of values in a region are less than the across site mean, though this results in marfish being excluded from W.

FW: exclude clad, mysid, corbic, sside/cent
W: exclude clad, corbic, marfish, sside/cent
N: exclude clad, potam, marfish
S: exclude mysid, potam, marfish

dataavail=focaldata %>% 
  gather(var, value, 4:length(fvars)) %>% 
  group_by(var) %>% 
  mutate(varmean=mean(value, na.rm=T)) %>% ungroup() %>% 
  group_by(region, var) %>% 
  summarize(
    propmissing=length(which(is.na(value)))/length(value),
    propzeros=length(which(value==0))/length(which(!is.na(value))),
    exclude=ifelse(quantile(value,probs = 0.95, na.rm = T)<mean(varmean),T,F)) %>% 
  as.data.frame()
## `summarise()` has grouped output by 'region'. You can override using the
## `.groups` argument.
#these variables should not be used (too many zeros)
filter(dataavail,propzeros>0.1 | exclude) %>% filter(var %in% c("mysid","hcope","pcope","rotif_m","clad"))
##     region   var propmissing  propzeros exclude
## 1 Far West  clad 0.141025641 0.95149254    TRUE
## 2 Far West mysid 0.137820513 0.21933086    TRUE
## 3    North  clad 0.012820513 0.14610390   FALSE
## 4    South mysid 0.006410256 0.08709677    TRUE
## 5     West  clad 0.009615385 0.26537217   FALSE
filter(dataavail,exclude) %>% filter(var %in% c("marfish_bsmt","potam","corbic"))
##     region          var propmissing propzeros exclude
## 1 Far West       corbic   0.1410256 1.0000000    TRUE
## 2    North marfish_bsmt   0.1891026 0.9762846    TRUE
## 3    North        potam   0.1378205 0.1486989    TRUE
## 4    South marfish_bsmt   0.1826923 1.0000000    TRUE
## 5    South        potam   0.1378205 0.9702602    TRUE
## 6     West       corbic   0.1378205 0.8066914    TRUE
## 7     West marfish_bsmt   0.1666667 0.2192308    TRUE

Time series plots

## Note: Using an external vector in selections is ambiguous.
## i Use `all_of(varnames)` instead of `varnames` to silence this message.
## i See <https://tidyselect.r-lib.org/reference/faq-external-vector.html>.
## This message is displayed once per session.

Other useful plots

Breakdown of total zooplankton biomass.

## Warning: Removed 272 rows containing missing values (position_stack).

Correlation between biomass and energy.

for(i in 1:length(regions)) {
  dtemp=filter(fdr,region==regions[i])
  print(regions[i])
  print(cor(dtemp$tzoop,dtemp$tzoop_e,use = "p"))
  print(cor(dtemp$hzoop,dtemp$hzoop_e,use = "p"))
  print(cor(dtemp$pzoop,dtemp$pzoop_e,use = "p"))
}
## [1] "Far West"
##           [,1]
## [1,] 0.9967037
##           [,1]
## [1,] 0.9969857
##           [,1]
## [1,] 0.9996106
## [1] "North"
##           [,1]
## [1,] 0.9958978
##           [,1]
## [1,] 0.9945197
##          [,1]
## [1,] 0.999494
## [1] "South"
##           [,1]
## [1,] 0.9967635
##           [,1]
## [1,] 0.9965366
##         [,1]
## [1,] 0.99925
## [1] "West"
##           [,1]
## [1,] 0.9964103
##          [,1]
## [1,] 0.994996
##           [,1]
## [1,] 0.9983814

Cross-correlation matrices

(only sig correlations shown… no correction for multiple comparisons)

## Warning: `expand_scale()` is deprecated; use `expansion()` instead.

## Warning: `expand_scale()` is deprecated; use `expansion()` instead.

## Warning: `expand_scale()` is deprecated; use `expansion()` instead.

## Warning: `expand_scale()` is deprecated; use `expansion()` instead.

## Warning: `expand_scale()` is deprecated; use `expansion()` instead.

## Warning: `expand_scale()` is deprecated; use `expansion()` instead.

Other notes:

Detrended fish indices are NOT correlated in S!

Nitrate and ammonia are positively correlated, max at lag 0 all regions.
Nitrate and dophos are positively correlated, max at lag 0 all regions.
Ammonia and dophos are positively correlated, lag 0 for FW and S, ammonia lags dphos by 3 months in W and N.

Chla nitrate neg correlated, lag 0.
Chla ammonia neg correlated, lag 0.
Chla dophos relationship unclear.

High flow 2-4 month prev = high chla

Hcope lags chla by 1, positive, except FW.
Clad seem to precede chla by 2, positive.
Amphi relationship unclear, prob bc not eating chla in water column.
In N and W, chla lags potam, negative. The opposite in W.

Mysid and hcope postive, lag 0.
In S and W, hcope lags pcope, negative.

Exploratory plots

Fish-centered model (upper trophic level aggregates)

modFW='hzoop~hb1*chla_1+hs1*hzoop_1+ht1*pzoop_1+ht2*potam_1+ht3*estfish_bsmt_1+ha1*flow+ha2*temp+ha3*turbid
        pzoop~pb1*hzoop_1+ps1*pzoop_1+pt1*potam_1+pt2*estfish_bsmt_1+pa1*flow+pa2*temp+pa3*turbid
        estfish_bsmt~fb1*hzoop_1+fb2*pzoop_1+fs1*estfish_bsmt_1+fa1*flow+fa2*temp+fa3*turbid+ft1*marfish_bsmt_1+ft2*sbass1_bsmt_1
        
        hb:=sqrt(hb1^2)
        hs:=sqrt(hs1^2)
        ht:=sqrt(ht1^2+ht2^2+ht3^2)
        ha:=sqrt(ha1^2+ha2^2+ha3^2)
        
        pb:=sqrt(pb1^2)
        ps:=sqrt(ps1^2)
        pt:=sqrt(pt1^2+pt2^2)
        pa:=sqrt(pa1^2+pa2^2+pa3^2)
        
        fb:=sqrt(fb1^2+fb2^2)
        fs:=sqrt(fs1^2)
        ft:=sqrt(ft1^2+ft2^2)
        fa:=sqrt(fa1^2+fa2^2+fa3^2)
'

modW='hzoop~hb1*chla_1+hs1*hzoop_1+ht1*pzoop_1+ht2*potam_1+ht3*estfish_bsmt_1+ha1*flow+ha2*temp+ha3*turbid
        pzoop~pb1*chla_1+pb2*hzoop_1+ps1*pzoop_1+pt1*potam_1+pt2*estfish_bsmt_1+pa1*flow+pa2*temp+pa3*turbid
        estfish_bsmt~fb1*hzoop_1+fb2*pzoop_1+fs1*estfish_bsmt_1+fa1*flow+fa2*temp+fa3*turbid+ft1*sbass1_bsmt_1
        
        hb:=sqrt(hb1^2)
        hs:=sqrt(hs1^2)
        ht:=sqrt(ht1^2+ht2^2+ht3^2)
        ha:=sqrt(ha1^2+ha2^2+ha3^2)
        
        pb:=sqrt(pb1^2+pb2^2)
        ps:=sqrt(ps1^2)
        pt:=sqrt(pt1^2+pt2^2)
        pa:=sqrt(pa1^2+pa2^2+pa3^2)
        
        fb:=sqrt(fb1^2+fb2^2)
        fs:=sqrt(fs1^2)
        ft:=sqrt(ft1^2)
        fa:=sqrt(fa1^2+fa2^2+fa3^2)
'

modN='hzoop~hb1*chla_1+hs1*hzoop_1+ht1*pzoop_1+ht2*corbic_1+ht3*estfish_bsmt_1+ha1*flow+ha2*temp+ha3*turbid
        pzoop~pb1*chla_1+pb2*hzoop_1+ps1*pzoop_1+pt1*corbic_1+pt2*estfish_bsmt_1+pa1*flow+pa2*temp+pa3*turbid
        estfish_bsmt~fb1*hzoop_1+fb2*pzoop_1+fs1*estfish_bsmt_1+fa1*flow+fa2*temp+fa3*turbid+ft1*sside_1+ft2*cent_1+ft3*sbass1_bsmt_1
        
        hb:=sqrt(hb1^2)
        hs:=sqrt(hs1^2)
        ht:=sqrt(ht1^2+ht2^2+ht3^2)
        ha:=sqrt(ha1^2+ha2^2+ha3^2)
        
        pb:=sqrt(pb1^2+pb2^2)
        ps:=sqrt(ps1^2)
        pt:=sqrt(pt1^2+pt2^2)
        pa:=sqrt(pa1^2+pa2^2+pa3^2)
        
        fb:=sqrt(fb1^2+fb2^2)
        fs:=sqrt(fs1^2)
        ft:=sqrt(ft1^2+ft2^2+ft3^2)
        fa:=sqrt(fa1^2+fa2^2+fa3^2)
'

modS='hzoop~hb1*chla_1+hs1*hzoop_1+ht1*pzoop_1+ht2*corbic_1+ht3*estfish_bsmt_1+ha1*flow+ha2*temp+ha3*turbid
        pzoop~pb1*chla_1+pb2*hzoop_1+ps1*pzoop_1+pt1*corbic_1+pt2*estfish_bsmt_1+pa1*flow+pa2*temp+pa3*turbid
        estfish_bsmt~fb1*chla_1+fb2*hzoop_1+fb3*pzoop_1+fs1*estfish_bsmt_1+fa1*flow+fa2*temp+fa3*turbid+ft1*sside_1+ft2*cent_1+ft3*sbass1_bsmt_1
        
        hb:=sqrt(hb1^2)
        hs:=sqrt(hs1^2)
        ht:=sqrt(ht1^2+ht2^2+ht3^2)
        ha:=sqrt(ha1^2+ha2^2+ha3^2)
        
        pb:=sqrt(pb1^2+pb2^2)
        ps:=sqrt(ps1^2)
        pt:=sqrt(pt1^2+pt2^2)
        pa:=sqrt(pa1^2+pa2^2+pa3^2)
        
        fb:=sqrt(fb1^2+fb2^2+fb3^2)
        fs:=sqrt(fs1^2)
        ft:=sqrt(ft1^2+ft2^2+ft3^2)
        fa:=sqrt(fa1^2+fa2^2+fa3^2)
'

modfitFW=sem(modFW, data=filter(fdr_ds,region=="Far West"))
modfitW=sem(modW, data=filter(fdr_ds,region=="West"))
modfitN=sem(modN, data=filter(fdr_ds,region=="North"))
modfitS=sem(modS, data=filter(fdr_ds,region=="South"))
summary(modfitFW, standardized=T, rsq=T)
## lavaan 0.6-10 ended normally after 14 iterations
## 
##   Estimator                                         ML
##   Optimization method                           NLMINB
##   Number of model parameters                        29
##                                                       
##                                                   Used       Total
##   Number of observations                           191         312
##                                                                   
## Model Test User Model:
##                                                       
##   Test statistic                                 7.216
##   Degrees of freedom                                 7
##   P-value (Chi-square)                           0.407
## 
## Parameter Estimates:
## 
##   Standard errors                             Standard
##   Information                                 Expected
##   Information saturated (h1) model          Structured
## 
## Regressions:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##   hzoop ~                                                               
##     chla_1   (hb1)    0.031    0.076    0.409    0.683    0.031    0.026
##     hzoop_1  (hs1)    0.315    0.065    4.859    0.000    0.315    0.327
##     pzoop_1  (ht1)    0.057    0.062    0.910    0.363    0.057    0.060
##     potam_1  (ht2)   -0.187    0.058   -3.216    0.001   -0.187   -0.210
##     estfs__1 (ht3)   -0.169    0.069   -2.442    0.015   -0.169   -0.168
##     flow     (ha1)   -0.032    0.075   -0.419    0.675   -0.032   -0.030
##     temp     (ha2)   -0.091    0.072   -1.257    0.209   -0.091   -0.086
##     turbid   (ha3)    0.050    0.081    0.616    0.538    0.050    0.044
##   pzoop ~                                                               
##     hzoop_1  (pb1)    0.050    0.067    0.751    0.453    0.050    0.050
##     pzoop_1  (ps1)    0.344    0.065    5.283    0.000    0.344    0.348
##     potam_1  (pt1)   -0.103    0.060   -1.707    0.088   -0.103   -0.110
##     estfs__1 (pt2)   -0.031    0.072   -0.432    0.666   -0.031   -0.030
##     flow     (pa1)    0.083    0.078    1.057    0.290    0.083    0.076
##     temp     (pa2)   -0.018    0.075   -0.245    0.807   -0.018   -0.017
##     turbid   (pa3)    0.251    0.084    2.998    0.003    0.251    0.215
##   estfish_bsmt ~                                                        
##     hzoop_1  (fb1)   -0.183    0.056   -3.261    0.001   -0.183   -0.198
##     pzoop_1  (fb2)    0.117    0.056    2.089    0.037    0.117    0.129
##     estfs__1 (fs1)    0.341    0.064    5.344    0.000    0.341    0.353
##     flow     (fa1)    0.090    0.068    1.323    0.186    0.090    0.090
##     temp     (fa2)   -0.034    0.065   -0.531    0.595   -0.034   -0.034
##     turbid   (fa3)    0.250    0.073    3.437    0.001    0.250    0.233
##     mrfsh__1 (ft1)    0.001    0.064    0.016    0.988    0.001    0.001
##     sbss1__1 (ft2)   -0.019    0.064   -0.293    0.769   -0.019   -0.019
## 
## Covariances:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##  .hzoop ~~                                                              
##    .pzoop            -0.030    0.058   -0.507    0.612   -0.030   -0.037
##    .estfish_bsmt     -0.048    0.050   -0.970    0.332   -0.048   -0.070
##  .pzoop ~~                                                              
##    .estfish_bsmt     -0.088    0.052   -1.693    0.090   -0.088   -0.123
## 
## Variances:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##    .hzoop             0.774    0.079    9.772    0.000    0.774    0.755
##    .pzoop             0.842    0.086    9.772    0.000    0.842    0.750
##    .estfish_bsmt      0.603    0.062    9.772    0.000    0.603    0.639
## 
## R-Square:
##                    Estimate
##     hzoop             0.245
##     pzoop             0.250
##     estfish_bsmt      0.361
## 
## Defined Parameters:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##     hb                0.031    0.076    0.409    0.683    0.031    0.026
##     hs                0.315    0.065    4.859    0.000    0.315    0.327
##     ht                0.258    0.057    4.498    0.000    0.258    0.276
##     ha                0.108    0.073    1.479    0.139    0.108    0.101
##     pb                0.050    0.067    0.751    0.453    0.050    0.050
##     ps                0.344    0.065    5.283    0.000    0.344    0.348
##     pt                0.107    0.058    1.847    0.065    0.107    0.114
##     pa                0.265    0.073    3.617    0.000    0.265    0.228
##     fb                0.217    0.058    3.715    0.000    0.217    0.236
##     fs                0.341    0.064    5.344    0.000    0.341    0.353
##     ft                0.019    0.064    0.295    0.768    0.019    0.019
##     fa                0.268    0.062    4.295    0.000    0.268    0.252
summary(modfitW, standardized=T, rsq=T)
## lavaan 0.6-10 ended normally after 17 iterations
## 
##   Estimator                                         ML
##   Optimization method                           NLMINB
##   Number of model parameters                        29
##                                                       
##                                                   Used       Total
##   Number of observations                           210         312
##                                                                   
## Model Test User Model:
##                                                       
##   Test statistic                                 2.747
##   Degrees of freedom                                 4
##   P-value (Chi-square)                           0.601
## 
## Parameter Estimates:
## 
##   Standard errors                             Standard
##   Information                                 Expected
##   Information saturated (h1) model          Structured
## 
## Regressions:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##   hzoop ~                                                               
##     chla_1   (hb1)    0.052    0.068    0.773    0.440    0.052    0.047
##     hzoop_1  (hs1)    0.417    0.071    5.897    0.000    0.417    0.400
##     pzoop_1  (ht1)    0.021    0.064    0.330    0.741    0.021    0.020
##     potam_1  (ht2)   -0.181    0.068   -2.651    0.008   -0.181   -0.168
##     estfs__1 (ht3)    0.020    0.063    0.317    0.752    0.020    0.019
##     flow     (ha1)    0.197    0.070    2.818    0.005    0.197    0.184
##     temp     (ha2)    0.005    0.061    0.089    0.929    0.005    0.005
##     turbid   (ha3)   -0.177    0.069   -2.587    0.010   -0.177   -0.163
##   pzoop ~                                                               
##     chla_1   (pb1)    0.195    0.065    3.021    0.003    0.195    0.181
##     hzoop_1  (pb2)    0.114    0.068    1.672    0.095    0.114    0.113
##     pzoop_1  (ps1)    0.418    0.062    6.752    0.000    0.418    0.414
##     potam_1  (pt1)   -0.091    0.065   -1.395    0.163   -0.091   -0.087
##     estfs__1 (pt2)    0.038    0.061    0.620    0.535    0.038    0.037
##     flow     (pa1)   -0.102    0.067   -1.515    0.130   -0.102   -0.098
##     temp     (pa2)    0.188    0.059    3.188    0.001    0.188    0.191
##     turbid   (pa3)    0.031    0.066    0.464    0.643    0.031    0.029
##   estfish_bsmt ~                                                        
##     hzoop_1  (fb1)    0.142    0.071    2.002    0.045    0.142    0.138
##     pzoop_1  (fb2)   -0.078    0.068   -1.146    0.252   -0.078   -0.076
##     estfs__1 (fs1)    0.175    0.072    2.429    0.015    0.175    0.169
##     flow     (fa1)   -0.219    0.073   -2.984    0.003   -0.219   -0.207
##     temp     (fa2)    0.020    0.064    0.317    0.751    0.020    0.020
##     turbid   (fa3)    0.243    0.071    3.441    0.001    0.243    0.228
##     sbss1__1 (ft1)    0.240    0.069    3.492    0.000    0.240    0.230
## 
## Covariances:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##  .hzoop ~~                                                              
##    .pzoop             0.177    0.049    3.588    0.000    0.177    0.256
##    .estfish_bsmt     -0.088    0.053   -1.662    0.096   -0.088   -0.115
##  .pzoop ~~                                                              
##    .estfish_bsmt      0.137    0.052    2.656    0.008    0.137    0.186
## 
## Variances:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##    .hzoop             0.720    0.070   10.247    0.000    0.720    0.675
##    .pzoop             0.667    0.065   10.247    0.000    0.667    0.669
##    .estfish_bsmt      0.811    0.079   10.247    0.000    0.811    0.785
## 
## R-Square:
##                    Estimate
##     hzoop             0.325
##     pzoop             0.331
##     estfish_bsmt      0.215
## 
## Defined Parameters:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##     hb                0.052    0.068    0.773    0.440    0.052    0.047
##     hs                0.417    0.071    5.897    0.000    0.417    0.400
##     ht                0.183    0.067    2.742    0.006    0.183    0.171
##     ha                0.265    0.076    3.474    0.001    0.265    0.246
##     pb                0.226    0.057    3.937    0.000    0.226    0.213
##     ps                0.418    0.062    6.752    0.000    0.418    0.414
##     pt                0.098    0.062    1.589    0.112    0.098    0.095
##     pa                0.216    0.062    3.477    0.001    0.216    0.217
##     fb                0.162    0.079    2.057    0.040    0.162    0.158
##     fs                0.175    0.072    2.429    0.015    0.175    0.169
##     ft                0.240    0.069    3.492    0.000    0.240    0.230
##     fa                0.328    0.081    4.031    0.000    0.328    0.309
summary(modfitN, standardized=T, rsq=T)
## lavaan 0.6-10 ended normally after 15 iterations
## 
##   Estimator                                         ML
##   Optimization method                           NLMINB
##   Number of model parameters                        31
##                                                       
##                                                   Used       Total
##   Number of observations                           193         312
##                                                                   
## Model Test User Model:
##                                                       
##   Test statistic                                 9.502
##   Degrees of freedom                                 8
##   P-value (Chi-square)                           0.302
## 
## Parameter Estimates:
## 
##   Standard errors                             Standard
##   Information                                 Expected
##   Information saturated (h1) model          Structured
## 
## Regressions:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##   hzoop ~                                                               
##     chla_1   (hb1)    0.041    0.073    0.564    0.573    0.041    0.038
##     hzoop_1  (hs1)    0.213    0.071    3.011    0.003    0.213    0.208
##     pzoop_1  (ht1)    0.033    0.073    0.446    0.656    0.033    0.032
##     corbic_1 (ht2)    0.004    0.068    0.056    0.956    0.004    0.004
##     estfs__1 (ht3)   -0.078    0.068   -1.143    0.253   -0.078   -0.083
##     flow     (ha1)    0.237    0.076    3.121    0.002    0.237    0.236
##     temp     (ha2)    0.108    0.066    1.630    0.103    0.108    0.111
##     turbid   (ha3)    0.196    0.070    2.796    0.005    0.196    0.190
##   pzoop ~                                                               
##     chla_1   (pb1)    0.268    0.064    4.165    0.000    0.268    0.246
##     hzoop_1  (pb2)    0.177    0.062    2.831    0.005    0.177    0.173
##     pzoop_1  (ps1)    0.233    0.065    3.592    0.000    0.233    0.229
##     corbic_1 (pt1)    0.030    0.060    0.501    0.616    0.030    0.030
##     estfs__1 (pt2)   -0.060    0.060   -0.996    0.319   -0.060   -0.064
##     flow     (pa1)   -0.435    0.067   -6.489    0.000   -0.435   -0.434
##     temp     (pa2)    0.081    0.059    1.377    0.169    0.081    0.083
##     turbid   (pa3)    0.003    0.062    0.048    0.962    0.003    0.003
##   estfish_bsmt ~                                                        
##     hzoop_1  (fb1)    0.154    0.074    2.089    0.037    0.154    0.141
##     pzoop_1  (fb2)    0.012    0.075    0.160    0.873    0.012    0.011
##     estfs__1 (fs1)    0.127    0.071    1.790    0.073    0.127    0.127
##     flow     (fa1)   -0.468    0.078   -5.996    0.000   -0.468   -0.436
##     temp     (fa2)   -0.017    0.067   -0.251    0.802   -0.017   -0.016
##     turbid   (fa3)    0.067    0.073    0.920    0.357    0.067    0.061
##     sside_1  (ft1)   -0.018    0.068   -0.260    0.795   -0.018   -0.017
##     cent_1   (ft2)   -0.127    0.069   -1.837    0.066   -0.127   -0.121
##     sbss1__1 (ft3)    0.095    0.071    1.331    0.183    0.095    0.090
## 
## Covariances:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##  .hzoop ~~                                                              
##    .pzoop             0.178    0.053    3.339    0.001    0.178    0.248
##    .estfish_bsmt     -0.057    0.059   -0.967    0.334   -0.057   -0.070
##  .pzoop ~~                                                              
##    .estfish_bsmt     -0.002    0.052   -0.047    0.962   -0.002   -0.003
## 
## Variances:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##    .hzoop             0.813    0.083    9.823    0.000    0.813    0.820
##    .pzoop             0.633    0.064    9.823    0.000    0.633    0.643
##    .estfish_bsmt      0.831    0.085    9.823    0.000    0.831    0.732
## 
## R-Square:
##                    Estimate
##     hzoop             0.180
##     pzoop             0.357
##     estfish_bsmt      0.268
## 
## Defined Parameters:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##     hb                0.041    0.073    0.564    0.573    0.041    0.038
##     hs                0.213    0.071    3.011    0.003    0.213    0.208
##     ht                0.085    0.075    1.133    0.257    0.085    0.089
##     ha                0.326    0.071    4.605    0.000    0.326    0.323
##     pb                0.321    0.062    5.164    0.000    0.321    0.301
##     ps                0.233    0.065    3.592    0.000    0.233    0.229
##     pt                0.067    0.063    1.074    0.283    0.067    0.071
##     pa                0.442    0.065    6.834    0.000    0.442    0.442
##     fb                0.155    0.072    2.138    0.032    0.155    0.142
##     fs                0.127    0.071    1.790    0.073    0.127    0.127
##     ft                0.160    0.063    2.515    0.012    0.160    0.152
##     fa                0.473    0.080    5.931    0.000    0.473    0.440
summary(modfitS, standardized=T, rsq=T)
## lavaan 0.6-10 ended normally after 14 iterations
## 
##   Estimator                                         ML
##   Optimization method                           NLMINB
##   Number of model parameters                        32
##                                                       
##                                                   Used       Total
##   Number of observations                           199         312
##                                                                   
## Model Test User Model:
##                                                       
##   Test statistic                                 5.655
##   Degrees of freedom                                 7
##   P-value (Chi-square)                           0.581
## 
## Parameter Estimates:
## 
##   Standard errors                             Standard
##   Information                                 Expected
##   Information saturated (h1) model          Structured
## 
## Regressions:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##   hzoop ~                                                               
##     chla_1   (hb1)    0.251    0.073    3.437    0.001    0.251    0.232
##     hzoop_1  (hs1)    0.208    0.070    2.986    0.003    0.208    0.198
##     pzoop_1  (ht1)   -0.023    0.077   -0.304    0.761   -0.023   -0.021
##     corbic_1 (ht2)    0.084    0.071    1.182    0.237    0.084    0.078
##     estfs__1 (ht3)    0.003    0.070    0.042    0.967    0.003    0.003
##     flow     (ha1)    0.204    0.072    2.825    0.005    0.204    0.186
##     temp     (ha2)    0.171    0.067    2.533    0.011    0.171    0.167
##     turbid   (ha3)   -0.043    0.069   -0.627    0.531   -0.043   -0.042
##   pzoop ~                                                               
##     chla_1   (pb1)    0.298    0.061    4.909    0.000    0.298    0.298
##     hzoop_1  (pb2)    0.138    0.058    2.391    0.017    0.138    0.142
##     pzoop_1  (ps1)    0.328    0.064    5.152    0.000    0.328    0.325
##     corbic_1 (pt1)   -0.060    0.058   -1.036    0.300   -0.060   -0.060
##     estfs__1 (pt2)    0.019    0.058    0.336    0.737    0.019    0.021
##     flow     (pa1)   -0.129    0.060   -2.137    0.033   -0.129   -0.126
##     temp     (pa2)   -0.034    0.056   -0.614    0.539   -0.034   -0.036
##     turbid   (pa3)    0.094    0.057    1.652    0.099    0.094    0.098
##   estfish_bsmt ~                                                        
##     chla_1   (fb1)    0.144    0.070    2.045    0.041    0.144    0.138
##     hzoop_1  (fb2)    0.138    0.068    2.030    0.042    0.138    0.136
##     pzoop_1  (fb3)   -0.047    0.073   -0.634    0.526   -0.047   -0.044
##     estfs__1 (fs1)    0.191    0.068    2.804    0.005    0.191    0.195
##     flow     (fa1)   -0.092    0.071   -1.312    0.190   -0.092   -0.087
##     temp     (fa2)   -0.027    0.065   -0.421    0.674   -0.027   -0.028
##     turbid   (fa3)    0.208    0.071    2.913    0.004    0.208    0.209
##     sside_1  (ft1)    0.055    0.065    0.856    0.392    0.055    0.055
##     cent_1   (ft2)   -0.076    0.067   -1.135    0.256   -0.076   -0.079
##     sbss1__1 (ft3)    0.067    0.068    0.976    0.329    0.067    0.067
## 
## Covariances:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##  .hzoop ~~                                                              
##    .pzoop             0.110    0.051    2.133    0.033    0.110    0.153
##    .estfish_bsmt      0.042    0.058    0.714    0.475    0.042    0.051
##  .pzoop ~~                                                              
##    .estfish_bsmt      0.133    0.049    2.680    0.007    0.133    0.193
## 
## Variances:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##    .hzoop             0.863    0.087    9.975    0.000    0.863    0.824
##    .pzoop             0.597    0.060    9.975    0.000    0.597    0.664
##    .estfish_bsmt      0.786    0.079    9.975    0.000    0.786    0.812
## 
## R-Square:
##                    Estimate
##     hzoop             0.176
##     pzoop             0.336
##     estfish_bsmt      0.188
## 
## Defined Parameters:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##     hb                0.251    0.073    3.437    0.001    0.251    0.232
##     hs                0.208    0.070    2.986    0.003    0.208    0.198
##     ht                0.087    0.072    1.203    0.229    0.087    0.081
##     ha                0.270    0.071    3.774    0.000    0.270    0.253
##     pb                0.329    0.058    5.688    0.000    0.329    0.330
##     ps                0.328    0.064    5.152    0.000    0.328    0.325
##     pt                0.063    0.057    1.102    0.270    0.063    0.064
##     pa                0.163    0.062    2.639    0.008    0.163    0.164
##     fb                0.204    0.070    2.926    0.003    0.204    0.199
##     fs                0.191    0.068    2.804    0.005    0.191    0.195
##     ft                0.115    0.065    1.774    0.076    0.115    0.118
##     fa                0.229    0.076    3.015    0.003    0.229    0.228
#modificationindices(modfitW, sort=T, maximum.number=20)
#residuals(modfitS)

labelsfarwest=createLabels(modfitFW, cnameslag)
labelswest=createLabels(modfitW, cnameslag)
labelsnorth=createLabels(modfitN, cnameslag)
labelssouth=createLabels(modfitS, cnameslag)


#FAR WEST
# myLavaanPlot(model=modfitFW, labels=labelsfarwest,
#                        node_options=list(shape="box", fontname="Helvetica"), 
#                        coefs=TRUE, stand=TRUE, covs=FALSE, sig=0.05, 
#                        width=c("regress","latent"),
#                        color=c("regress","latent"))

upper_plot_far_west <- createGraph(fit=modfitFW, 
                                   reference_df=cnameslag, 
                                   model_type="monthly_upper_trophic",
                                   title="Far West",
                                   manual_port_settings=TRUE)
upper_plot_far_west
#WEST
# myLavaanPlot(model=modfitW, labels=labelswest,
#                        node_options=list(shape="box", fontname="Helvetica"), 
#                        coefs=TRUE, stand=TRUE, covs=FALSE, sig=0.05, 
#                        width=c("regress","latent"),
#                        color=c("regress","latent"))

upper_plot_west <- createGraph(fit=modfitW, 
                               reference_df=cnameslag, 
                               model_type="monthly_upper_trophic",
                               title="West",
                               manual_port_settings=TRUE)
upper_plot_west
#NORTH
# myLavaanPlot(model=modfitN, labels=labelsnorth,
#                        node_options=list(shape="box", fontname="Helvetica"), 
#                        coefs=TRUE, stand=TRUE, covs=FALSE, sig=0.05, 
#                        width=c("regress","latent"),
#                        color=c("regress","latent"))

upper_plot_north <- createGraph(fit=modfitN, 
                                reference_df=cnameslag, 
                                model_type="monthly_upper_trophic",
                                title="North",
                                manual_port_settings=TRUE)
upper_plot_north
#SOUTH
# myLavaanPlot(model=modfitS, labels=labelssouth,
#                        node_options=list(shape="box", fontname="Helvetica"), 
#                        coefs=TRUE, stand=TRUE, covs=FALSE, sig=0.05, 
#                        width=c("regress","latent"),
#                        color=c("regress","latent"))

upper_plot_south <- createGraph(fit=modfitS, 
                                reference_df=cnameslag, 
                                model_type="monthly_upper_trophic",
                                title="South",
                                manual_port_settings=TRUE)
upper_plot_south

Save updated SEM diagrams

Total effects

ssFW=standardizedsolution(modfitFW) %>% mutate(region="Far West")
ssW=standardizedsolution(modfitW) %>% mutate(region="West")
ssN=standardizedsolution(modfitN) %>% mutate(region="North")
ssS=standardizedsolution(modfitS) %>% mutate(region="South")

ssut=rbind(ssFW,ssW,ssN,ssS) %>% filter(op==":=") %>% select(region,lhs,est.std:ci.upper) %>% 
  separate(lhs,c("variable","influence"), sep=1) %>% 
  mutate(variable=case_when(variable=="h" ~ "herbivorous\nzooplankton",
                            variable=="p" ~ "predatory\nzooplankton",
                            variable=="f" ~ "estuarine\nfishes"),
         influence=case_when(influence=="b" ~ "bottom-up",
                            influence=="t" ~ "top-down",
                            influence=="s" ~ "self-regulation",
                            influence=="a" ~ "abiotic drivers"),
         region=factor(region, levels=regionorder),
         influence=factor(influence, levels=c("self-regulation","bottom-up","top-down","abiotic drivers")),
         variable=factor(variable,levels=c("estuarine\nfishes","predatory\nzooplankton","herbivorous\nzooplankton")),
         sig=ifelse(pvalue<0.05,"*",""))

ggplot(ssut,aes(x=influence,y=est.std)) +
  facet_grid(variable~region) +
  geom_errorbar(aes(ymin=ci.lower, ymax=ci.upper),width=0.5) +
  geom_point() +
  geom_text(aes(y=ci.upper+0.05, label=sig)) +
  geom_hline(yintercept = 0) +
  theme_bw() + theme(axis.text.x=element_text(angle=90, vjust=0.5, hjust=1)) +
  labs(y="total effect (standardized)")

ggsave("./fig_output/uteffects.png",width = 6,height=5)

Phytoplankton-centered model (lower trophic level aggregates)

modFW='din~ns1*din_1+nt1*chla+nn1*hzoop_1+nn2*pzoop_1+nn3*potam_1+na1*flow+na2*temp+na3*turbid
        chla~cb1*din_1+cs1*chla_1+ct1*hzoop_1+ct2*potam_1+ca1*flow+ca2*temp+ca3*turbid
        potam~lb1*chla_1+lb2*hzoop_1+lb3*pzoop_1+ls1*potam_1+la1*flow+la2*temp+la3*turbid
        
        ns:=sqrt(ns1^2)
        nt:=sqrt(nt1^2)
        nn:=sqrt(nn1^2+nn2^2+nn3^2)
        na:=sqrt(na1^2+na2^2+na3^2)
        
        cb:=sqrt(cb1^2)
        cs:=sqrt(cs1^2)
        ct:=sqrt(ct1^2+ct2^2)
        ca:=sqrt(ca1^2+ca2^2+ca3^2)
        
        lb:=sqrt(lb1^2+lb2^2+lb3^2)
        ls:=sqrt(ls1^2)
        la:=sqrt(la1^2+la2^2+la3^2)
'

modW='din~ns1*din_1+nt1*chla+nn1*hzoop_1+nn2*pzoop_1+nn3*potam_1+na1*flow+na2*temp+na3*turbid
        chla~cb1*din_1+cs1*chla_1+ct1*hzoop_1+ct2*potam_1+ca1*flow+ca2*temp+ca3*turbid
        potam~lb1*din_1+lb2*chla_1+lb3*hzoop_1+lb4*pzoop_1+ls1*potam_1+la1*flow+la2*temp+la3*turbid
        
        ns:=sqrt(ns1^2)
        nt:=sqrt(nt1^2)
        nn:=sqrt(nn1^2+nn2^2+nn3^2)
        na:=sqrt(na1^2+na2^2+na3^2)
        
        cb:=sqrt(cb1^2)
        cs:=sqrt(cs1^2)
        ct:=sqrt(ct1^2+ct2^2)
        ca:=sqrt(ca1^2+ca2^2+ca3^2)
        
        lb:=sqrt(lb1^2+lb2^2+lb3^2+lb4^2)
        ls:=sqrt(ls1^2)
        la:=sqrt(la1^2+la2^2+la3^2)
'

modN='din~ns1*din_1+nt1*chla+nn1*hzoop_1+nn2*pzoop_1+nn3*corbic_1+na1*flow+na2*temp+na3*turbid
        chla~cb1*din_1+cs1*chla_1+ct1*hzoop_1+ct2*corbic_1+ct3*pzoop_1+ca1*flow+ca2*temp+ca3*turbid
        corbic~lb1*chla_1+lb2*hzoop_1+lb3*pzoop_1+ls1*corbic_1+la1*flow+la2*temp+la3*turbid
        
        ns:=sqrt(ns1^2)
        nt:=sqrt(nt1^2)
        nn:=sqrt(nn1^2+nn2^2+nn3^2)
        na:=sqrt(na1^2+na2^2+na3^2)
        
        cb:=sqrt(cb1^2)
        cs:=sqrt(cs1^2)
        ct:=sqrt(ct1^2+ct2^2+ct3^2)
        ca:=sqrt(ca1^2+ca2^2+ca3^2)
        
        lb:=sqrt(lb1^2+lb2^2+lb3^2)
        ls:=sqrt(ls1^2)
        la:=sqrt(la1^2+la2^2+la3^2)
'

modS='din~ns1*din_1+nt1*chla+nn1*hzoop_1+nn2*pzoop_1+nn3*corbic_1+na1*flow+na2*temp+na3*turbid
        chla~cb1*din_1+cs1*chla_1+ct1*hzoop_1+ct2*corbic_1+ca1*flow+ca2*temp+ca3*turbid
        corbic~lb1*chla_1+lb2*hzoop_1+lb3*pzoop_1+ls1*corbic_1+la1*flow+la2*temp+la3*turbid
        
        ns:=sqrt(ns1^2)
        nt:=sqrt(nt1^2)
        nn:=sqrt(nn1^2+nn2^2+nn3^2)
        na:=sqrt(na1^2+na2^2+na3^2)
        
        cb:=sqrt(cb1^2)
        cs:=sqrt(cs1^2)
        ct:=sqrt(ct1^2+ct2^2)
        ca:=sqrt(ca1^2+ca2^2+ca3^2)
        
        lb:=sqrt(lb1^2+lb2^2+lb3^2)
        ls:=sqrt(ls1^2)
        la:=sqrt(la1^2+la2^2+la3^2)
'

modfitFW=sem(modFW, data=filter(fdr_ds,region=="Far West"))
modfitW=sem(modW, data=filter(fdr_ds,region=="West"))
modfitN=sem(modN, data=filter(fdr_ds,region=="North"))
modfitS=sem(modS, data=filter(fdr_ds,region=="South"))
summary(modfitFW, standardized=T, rsq=T)
## lavaan 0.6-10 ended normally after 12 iterations
## 
##   Estimator                                         ML
##   Optimization method                           NLMINB
##   Number of model parameters                        26
##                                                       
##                                                   Used       Total
##   Number of observations                           234         312
##                                                                   
## Model Test User Model:
##                                                       
##   Test statistic                                 1.418
##   Degrees of freedom                                 4
##   P-value (Chi-square)                           0.841
## 
## Parameter Estimates:
## 
##   Standard errors                             Standard
##   Information                                 Expected
##   Information saturated (h1) model          Structured
## 
## Regressions:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##   din ~                                                                 
##     din_1    (ns1)    0.426    0.057    7.402    0.000    0.426    0.426
##     chla     (nt1)   -0.163    0.072   -2.274    0.023   -0.163   -0.130
##     hzoop_1  (nn1)    0.033    0.059    0.553    0.580    0.033    0.033
##     pzoop_1  (nn2)   -0.022    0.058   -0.383    0.702   -0.022   -0.023
##     potam_1  (nn3)   -0.005    0.057   -0.090    0.928   -0.005   -0.005
##     flow     (na1)   -0.012    0.067   -0.182    0.856   -0.012   -0.012
##     temp     (na2)   -0.156    0.064   -2.437    0.015   -0.156   -0.149
##     turbid   (na3)   -0.139    0.068   -2.044    0.041   -0.139   -0.130
##   chla ~                                                                
##     din_1    (cb1)    0.016    0.051    0.312    0.755    0.016    0.020
##     chla_1   (cs1)    0.258    0.063    4.106    0.000    0.258    0.263
##     hzoop_1  (ct1)   -0.012    0.052   -0.225    0.822   -0.012   -0.015
##     potam_1  (ct2)   -0.018    0.050   -0.356    0.722   -0.018   -0.023
##     flow     (ca1)    0.062    0.058    1.078    0.281    0.062    0.073
##     temp     (ca2)    0.128    0.056    2.277    0.023    0.128    0.153
##     turbid   (ca3)   -0.047    0.060   -0.790    0.429   -0.047   -0.055
##   potam ~                                                               
##     chla_1   (lb1)    0.066    0.060    1.102    0.271    0.066    0.052
##     hzoop_1  (lb2)   -0.080    0.051   -1.561    0.119   -0.080   -0.077
##     pzoop_1  (lb3)   -0.162    0.050   -3.243    0.001   -0.162   -0.160
##     potam_1  (ls1)    0.628    0.048   13.003    0.000    0.628    0.628
##     flow     (la1)    0.112    0.057    1.959    0.050    0.112    0.102
##     temp     (la2)   -0.043    0.054   -0.787    0.432   -0.043   -0.040
##     turbid   (la3)    0.038    0.058    0.656    0.512    0.038    0.035
## 
## Covariances:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##  .din ~~                                                                
##    .potam            -0.044    0.044   -1.016    0.310   -0.044   -0.067
## 
## Variances:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##    .din               0.778    0.072   10.817    0.000    0.778    0.753
##    .chla              0.602    0.056   10.817    0.000    0.602    0.908
##    .potam             0.567    0.052   10.817    0.000    0.567    0.517
## 
## R-Square:
##                    Estimate
##     din               0.247
##     chla              0.092
##     potam             0.483
## 
## Defined Parameters:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##     ns                0.426    0.057    7.402    0.000    0.426    0.426
##     nt                0.163    0.072    2.274    0.023    0.163    0.130
##     nn                0.040    0.061    0.658    0.511    0.040    0.040
##     na                0.209    0.072    2.893    0.004    0.209    0.199
##     cb                0.016    0.051    0.312    0.755    0.016    0.020
##     cs                0.258    0.063    4.106    0.000    0.258    0.263
##     ct                0.021    0.055    0.385    0.700    0.021    0.027
##     ca                0.150    0.057    2.607    0.009    0.150    0.178
##     lb                0.192    0.049    3.891    0.000    0.192    0.185
##     ls                0.628    0.048   13.003    0.000    0.628    0.628
##     la                0.126    0.049    2.580    0.010    0.126    0.115
summary(modfitW, standardized=T, rsq=T)
## lavaan 0.6-10 ended normally after 14 iterations
## 
##   Estimator                                         ML
##   Optimization method                           NLMINB
##   Number of model parameters                        27
##                                                       
##                                                   Used       Total
##   Number of observations                           257         312
##                                                                   
## Model Test User Model:
##                                                       
##   Test statistic                                 6.550
##   Degrees of freedom                                 3
##   P-value (Chi-square)                           0.088
## 
## Parameter Estimates:
## 
##   Standard errors                             Standard
##   Information                                 Expected
##   Information saturated (h1) model          Structured
## 
## Regressions:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##   din ~                                                                 
##     din_1    (ns1)    0.410    0.052    7.856    0.000    0.410    0.410
##     chla     (nt1)   -0.144    0.052   -2.763    0.006   -0.144   -0.130
##     hzoop_1  (nn1)    0.018    0.051    0.347    0.729    0.018    0.018
##     pzoop_1  (nn2)    0.041    0.048    0.847    0.397    0.041    0.041
##     potam_1  (nn3)    0.078    0.053    1.473    0.141    0.078    0.078
##     flow     (na1)   -0.358    0.054   -6.608    0.000   -0.358   -0.349
##     temp     (na2)    0.027    0.047    0.580    0.562    0.027    0.027
##     turbid   (na3)    0.106    0.050    2.115    0.034    0.106    0.106
##   chla ~                                                                
##     din_1    (cb1)   -0.126    0.062   -2.029    0.042   -0.126   -0.140
##     chla_1   (cs1)    0.149    0.065    2.301    0.021    0.149    0.149
##     hzoop_1  (ct1)    0.092    0.058    1.581    0.114    0.092    0.105
##     potam_1  (ct2)    0.035    0.062    0.558    0.577    0.035    0.039
##     flow     (ca1)    0.049    0.063    0.774    0.439    0.049    0.053
##     temp     (ca2)   -0.059    0.055   -1.083    0.279   -0.059   -0.067
##     turbid   (ca3)   -0.029    0.059   -0.480    0.631   -0.029   -0.032
##   potam ~                                                               
##     din_1    (lb1)    0.073    0.044    1.672    0.095    0.073    0.072
##     chla_1   (lb2)   -0.008    0.045   -0.165    0.869   -0.008   -0.007
##     hzoop_1  (lb3)   -0.031    0.043   -0.710    0.477   -0.031   -0.031
##     pzoop_1  (lb4)    0.078    0.040    1.942    0.052    0.078    0.078
##     potam_1  (ls1)    0.703    0.044   16.008    0.000    0.703    0.698
##     flow     (la1)   -0.108    0.045   -2.405    0.016   -0.108   -0.104
##     temp     (la2)   -0.011    0.039   -0.284    0.777   -0.011   -0.011
##     turbid   (la3)   -0.079    0.042   -1.903    0.057   -0.079   -0.078
## 
## Covariances:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##  .din ~~                                                                
##    .potam             0.038    0.027    1.401    0.161    0.038    0.088
## 
## Variances:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##    .din               0.523    0.046   11.336    0.000    0.523    0.525
##    .chla              0.726    0.064   11.336    0.000    0.726    0.900
##    .potam             0.358    0.032   11.336    0.000    0.358    0.351
## 
## R-Square:
##                    Estimate
##     din               0.475
##     chla              0.100
##     potam             0.649
## 
## Defined Parameters:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##     ns                0.410    0.052    7.856    0.000    0.410    0.410
##     nt                0.144    0.052    2.763    0.006    0.144    0.130
##     nn                0.090    0.053    1.686    0.092    0.090    0.090
##     na                0.374    0.056    6.643    0.000    0.374    0.366
##     cb                0.126    0.062    2.029    0.042    0.126    0.140
##     cs                0.149    0.065    2.301    0.021    0.149    0.149
##     ct                0.099    0.063    1.562    0.118    0.099    0.112
##     ca                0.082    0.062    1.333    0.183    0.082    0.091
##     lb                0.112    0.043    2.598    0.009    0.112    0.111
##     ls                0.703    0.044   16.008    0.000    0.703    0.698
##     la                0.134    0.040    3.337    0.001    0.134    0.130
summary(modfitN, standardized=T, rsq=T)
## lavaan 0.6-10 ended normally after 11 iterations
## 
##   Estimator                                         ML
##   Optimization method                           NLMINB
##   Number of model parameters                        27
##                                                       
##                                                   Used       Total
##   Number of observations                           255         312
##                                                                   
## Model Test User Model:
##                                                       
##   Test statistic                                 5.353
##   Degrees of freedom                                 3
##   P-value (Chi-square)                           0.148
## 
## Parameter Estimates:
## 
##   Standard errors                             Standard
##   Information                                 Expected
##   Information saturated (h1) model          Structured
## 
## Regressions:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##   din ~                                                                 
##     din_1    (ns1)    0.129    0.053    2.415    0.016    0.129    0.130
##     chla     (nt1)   -0.173    0.050   -3.484    0.000   -0.173   -0.174
##     hzoop_1  (nn1)    0.051    0.052    0.991    0.322    0.051    0.051
##     pzoop_1  (nn2)    0.176    0.054    3.239    0.001    0.176    0.174
##     corbic_1 (nn3)   -0.027    0.051   -0.521    0.602   -0.027   -0.026
##     flow     (na1)   -0.469    0.057   -8.188    0.000   -0.469   -0.460
##     temp     (na2)    0.028    0.051    0.539    0.590    0.028    0.028
##     turbid   (na3)    0.055    0.049    1.127    0.260    0.055    0.056
##   chla ~                                                                
##     din_1    (cb1)    0.025    0.066    0.374    0.708    0.025    0.025
##     chla_1   (cs1)    0.279    0.060    4.643    0.000    0.279    0.281
##     hzoop_1  (ct1)   -0.053    0.063   -0.848    0.396   -0.053   -0.053
##     corbic_1 (ct2)    0.016    0.062    0.266    0.790    0.016    0.016
##     pzoop_1  (ct3)   -0.169    0.066   -2.567    0.010   -0.169   -0.165
##     flow     (ca1)   -0.054    0.069   -0.777    0.437   -0.054   -0.052
##     temp     (ca2)    0.136    0.061    2.213    0.027    0.136    0.136
##     turbid   (ca3)    0.078    0.059    1.312    0.190    0.078    0.079
##   corbic ~                                                              
##     chla_1   (lb1)    0.003    0.053    0.058    0.954    0.003    0.003
##     hzoop_1  (lb2)    0.015    0.056    0.265    0.791    0.015    0.015
##     pzoop_1  (lb3)   -0.012    0.058   -0.199    0.842   -0.012   -0.012
##     corbic_1 (ls1)    0.463    0.056    8.313    0.000    0.463    0.460
##     flow     (la1)    0.092    0.060    1.536    0.124    0.092    0.091
##     temp     (la2)   -0.034    0.055   -0.612    0.540   -0.034   -0.034
##     turbid   (la3)   -0.117    0.053   -2.214    0.027   -0.117   -0.121
## 
## Covariances:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##  .din ~~                                                                
##    .corbic           -0.017    0.041   -0.422    0.673   -0.017   -0.026
## 
## Variances:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##    .din               0.602    0.053   11.292    0.000    0.602    0.610
##    .chla              0.882    0.078   11.292    0.000    0.882    0.879
##    .corbic            0.715    0.063   11.292    0.000    0.715    0.740
## 
## R-Square:
##                    Estimate
##     din               0.390
##     chla              0.121
##     corbic            0.260
## 
## Defined Parameters:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##     ns                0.129    0.053    2.415    0.016    0.129    0.130
##     nt                0.173    0.050    3.484    0.000    0.173    0.174
##     nn                0.185    0.050    3.668    0.000    0.185    0.183
##     na                0.473    0.057    8.232    0.000    0.473    0.464
##     cb                0.025    0.066    0.374    0.708    0.025    0.025
##     cs                0.279    0.060    4.643    0.000    0.279    0.281
##     ct                0.178    0.061    2.914    0.004    0.178    0.174
##     ca                0.165    0.061    2.726    0.006    0.165    0.165
##     lb                0.019    0.063    0.305    0.761    0.019    0.019
##     ls                0.463    0.056    8.313    0.000    0.463    0.460
##     la                0.152    0.057    2.687    0.007    0.152    0.155
summary(modfitS, standardized=T, rsq=T)
## lavaan 0.6-10 ended normally after 10 iterations
## 
##   Estimator                                         ML
##   Optimization method                           NLMINB
##   Number of model parameters                        26
##                                                       
##                                                   Used       Total
##   Number of observations                           256         312
##                                                                   
## Model Test User Model:
##                                                       
##   Test statistic                                 2.594
##   Degrees of freedom                                 4
##   P-value (Chi-square)                           0.628
## 
## Parameter Estimates:
## 
##   Standard errors                             Standard
##   Information                                 Expected
##   Information saturated (h1) model          Structured
## 
## Regressions:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##   din ~                                                                 
##     din_1    (ns1)    0.202    0.061    3.304    0.001    0.202    0.203
##     chla     (nt1)    0.026    0.059    0.434    0.664    0.026    0.025
##     hzoop_1  (nn1)   -0.021    0.064   -0.321    0.748   -0.021   -0.019
##     pzoop_1  (nn2)    0.027    0.064    0.419    0.675    0.027    0.025
##     corbic_1 (nn3)    0.072    0.060    1.209    0.227    0.072    0.072
##     flow     (na1)   -0.006    0.061   -0.106    0.916   -0.006   -0.006
##     temp     (na2)    0.096    0.060    1.608    0.108    0.096    0.094
##     turbid   (na3)    0.252    0.063    4.014    0.000    0.252    0.250
##   chla ~                                                                
##     din_1    (cb1)   -0.007    0.062   -0.117    0.907   -0.007   -0.007
##     chla_1   (cs1)    0.286    0.061    4.725    0.000    0.286    0.286
##     hzoop_1  (ct1)    0.073    0.064    1.139    0.255    0.073    0.070
##     corbic_1 (ct2)    0.086    0.060    1.430    0.153    0.086    0.087
##     flow     (ca1)   -0.117    0.061   -1.917    0.055   -0.117   -0.115
##     temp     (ca2)    0.020    0.059    0.344    0.731    0.020    0.020
##     turbid   (ca3)    0.016    0.063    0.245    0.807    0.016    0.016
##   corbic ~                                                              
##     chla_1   (lb1)    0.054    0.059    0.913    0.361    0.054    0.054
##     hzoop_1  (lb2)   -0.030    0.061   -0.495    0.621   -0.030   -0.029
##     pzoop_1  (lb3)   -0.041    0.063   -0.649    0.517   -0.041   -0.038
##     corbic_1 (ls1)    0.316    0.058    5.486    0.000    0.316    0.319
##     flow     (la1)    0.082    0.058    1.409    0.159    0.082    0.081
##     temp     (la2)   -0.078    0.058   -1.350    0.177   -0.078   -0.077
##     turbid   (la3)    0.185    0.058    3.200    0.001    0.185    0.185
## 
## Covariances:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##  .din ~~                                                                
##    .corbic           -0.074    0.053   -1.405    0.160   -0.074   -0.088
## 
## Variances:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##    .din               0.869    0.077   11.314    0.000    0.869    0.845
##    .chla              0.880    0.078   11.314    0.000    0.880    0.881
##    .corbic            0.812    0.072   11.314    0.000    0.812    0.808
## 
## R-Square:
##                    Estimate
##     din               0.155
##     chla              0.119
##     corbic            0.192
## 
## Defined Parameters:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##     ns                0.202    0.061    3.304    0.001    0.202    0.203
##     nt                0.026    0.059    0.434    0.664    0.026    0.025
##     nn                0.080    0.063    1.272    0.203    0.080    0.079
##     na                0.270    0.064    4.232    0.000    0.270    0.267
##     cb                0.007    0.062    0.117    0.907    0.007    0.007
##     cs                0.286    0.061    4.725    0.000    0.286    0.286
##     ct                0.113    0.059    1.912    0.056    0.113    0.112
##     ca                0.119    0.061    1.942    0.052    0.119    0.118
##     lb                0.074    0.066    1.127    0.260    0.074    0.072
##     ls                0.316    0.058    5.486    0.000    0.316    0.319
##     la                0.217    0.055    3.921    0.000    0.217    0.217
#modificationindices(modfitW, sort=T, maximum.number=20)
#residuals(modfitW)

labelsfarwest=createLabels(modfitFW, cnameslag)
labelswest=createLabels(modfitW, cnameslag)
labelsnorth=createLabels(modfitN, cnameslag)
labelssouth=createLabels(modfitS, cnameslag)

#FAR WEST
# myLavaanPlot(model=modfitFW, labels=labelsfarwest,
#                        node_options=list(shape="box", fontname="Helvetica"), 
#                        coefs=TRUE, stand=TRUE, covs=FALSE, sig=0.05, 
#                        width=c("regress","latent"),
#                        color=c("regress","latent"))

lower_plot_far_west <- createGraph(fit=modfitFW, 
                                   reference_df=cnameslag, 
                                   model_type="monthly_lower_trophic",
                                   title="Far West",
                                   manual_port_settings=TRUE)
lower_plot_far_west
#WEST
# myLavaanPlot(model=modfitW, labels=labelswest,
#                        node_options=list(shape="box", fontname="Helvetica"), 
#                        coefs=TRUE, stand=TRUE, covs=FALSE, sig=0.05, 
#                        width=c("regress","latent"),
#                        color=c("regress","latent"))

lower_plot_west <- createGraph(fit=modfitW, 
                               reference_df=cnameslag, 
                               model_type="monthly_lower_trophic",
                               title="West",
                               manual_port_settings=TRUE)
lower_plot_west
#NORTH
# myLavaanPlot(model=modfitN, labels=labelsnorth,
#                        node_options=list(shape="box", fontname="Helvetica"), 
#                        coefs=TRUE, stand=TRUE, covs=FALSE, sig=0.05, 
#                        width=c("regress","latent"),
#                        color=c("regress","latent"))

lower_plot_north <- createGraph(fit=modfitN, 
                                reference_df=cnameslag, 
                                model_type="monthly_lower_trophic",
                                title="North",
                                manual_port_settings=TRUE)
lower_plot_north
#SOUTH
# myLavaanPlot(model=modfitS, labels=labelssouth,
#                        node_options=list(shape="box", fontname="Helvetica"), 
#                        coefs=TRUE, stand=TRUE, covs=FALSE, sig=0.05, 
#                        width=c("regress","latent"),
#                        color=c("regress","latent"))

lower_plot_south <- createGraph(fit=modfitS, 
                                reference_df=cnameslag, 
                                model_type="monthly_lower_trophic",
                                title="South",
                                manual_port_settings=TRUE)
lower_plot_south

Save updated SEM diagrams

Total effects

ssFW=standardizedsolution(modfitFW) %>% mutate(region="Far West")
ssW=standardizedsolution(modfitW) %>% mutate(region="West")
ssN=standardizedsolution(modfitN) %>% mutate(region="North")
ssS=standardizedsolution(modfitS) %>% mutate(region="South")

sslt=rbind(ssFW,ssW,ssN,ssS) %>% filter(op==":=") %>% select(region,lhs,est.std:ci.upper) %>% 
  separate(lhs,c("variable","influence"), sep=1) %>% 
  mutate(variable=case_when(variable=="n" ~ "DIN",
                            variable=="c" ~ "phytoplankton",
                            variable=="l" ~ "clams"),
         influence=case_when(influence=="b" ~ "bottom-up",
                            influence=="t" ~ "top-down",
                            influence=="s" ~ "self-regulation",
                            influence=="a" ~ "abiotic drivers",
                            influence=="n" ~ "nutrient cycling"),
         region=factor(region, levels=regionorder),
         influence=factor(influence, levels=c("self-regulation","bottom-up","top-down","abiotic drivers","nutrient cycling")),
         variable=factor(variable,levels=c("clams","phytoplankton","DIN")),
         sig=ifelse(pvalue<0.05,"*",""))

ggplot(sslt,aes(x=influence,y=est.std)) +
  facet_grid(variable~region) +
  geom_errorbar(aes(ymin=ci.lower, ymax=ci.upper),width=0.5) +
  geom_point() +
  geom_text(aes(y=ci.upper+0.05, label=sig)) +
  geom_hline(yintercept = 0) +
  theme_bw() + theme(axis.text.x=element_text(angle=90, vjust=0.5, hjust=1)) +
  labs(y="total effect (standardized)")

ggsave("./fig_output/lteffects.png",width = 6,height=5)

Zooplankton-centered model (individual groups)

#1
# modFW='chla~chla_1+hcope_1+amphi_m_1+potam_1+flow+turbid+temp
#        hcope~chla_1+hcope_1+pcope_1+potam_1+flow+turbid+temp+estfish_bsmt_1
#        amphi_m~chla_1+amphi_m_1+flow+turbid+temp+estfish_bsmt_1
#        pcope~hcope_1+pcope_1+potam_1+flow+turbid+temp+estfish_bsmt_1
# '
# modW='chla~chla_1+hcope_1+amphi_m_1+potam_1+flow+turbid+temp+mysid_1
#        hcope~chla_1+hcope_1+pcope_1+mysid_1+potam_1+flow+turbid+temp+estfish_bsmt_1
#        amphi_m~chla_1+amphi_m_1+mysid_1+flow+turbid+temp+estfish_bsmt_1
#        pcope~hcope_1+pcope_1+mysid_1+potam_1+flow+turbid+temp+estfish_bsmt_1
#        mysid~chla_1+hcope_1+pcope_1+amphi_m_1+mysid_1+flow+turbid+temp+estfish_bsmt_1
# '
# modN='chla~chla_1+hcope_1+amphi_m_1+corbic_1+flow+turbid+temp
#        hcope~chla_1+hcope_1+pcope_1+mysid_1+corbic_1+flow+turbid+temp+estfish_bsmt_1
#        amphi_m~chla_1+amphi_m_1+flow+turbid+temp+estfish_bsmt_1
#        pcope~hcope_1+pcope_1+mysid_1+corbic_1+flow+turbid+temp+estfish_bsmt_1
#        mysid~hcope_1+pcope_1+mysid_1+amphi_m_1+flow+turbid+temp+estfish_bsmt_1
# '
# modS='chla~chla_1+hcope_1+clad_1+corbic_1+flow+turbid+temp
#        hcope~chla_1+hcope_1+pcope_1+corbic_1+flow+turbid+temp+estfish_bsmt_1
#        clad~chla_1+clad_1+pcope_1+flow+turbid+temp+estfish_bsmt_1
#        amphi_m~chla_1+amphi_m_1+flow+turbid+temp+estfish_bsmt_1
#        pcope~chla_1+hcope_1+clad_1+pcope_1+corbic_1+flow+turbid+temp+estfish_bsmt_1
# '
#2
modFW='chla~chla_1+hcope_1+amphi_m_1+rotif_m_1+potam_1+flow+turbid+temp
       hcope~chla_1+hcope_1+pcope_1+potam_1+flow+turbid+temp+estfish_bsmt_1
       amphi_m~chla_1+amphi_m_1+flow+turbid+temp+estfish_bsmt_1
       rotif_m~chla_1+rotif_m_1+flow+turbid+temp+estfish_bsmt_1
       pcope~hcope_1+pcope_1+potam_1+flow+turbid+temp+estfish_bsmt_1
       estfish_bsmt~estfish_bsmt_1+hcope_1+pcope_1+amphi_m_1+rotif_m_1+flow+turbid+temp
'
modW='chla~chla_1+hcope_1+amphi_m_1+rotif_m_1+potam_1+flow+turbid+temp+mysid_1
       hcope~chla_1+hcope_1+pcope_1+mysid_1+potam_1+flow+turbid+temp+estfish_bsmt_1+rotif_m_1
       amphi_m~chla_1+amphi_m_1+mysid_1+flow+turbid+temp+estfish_bsmt_1
       rotif_m~chla_1+rotif_m_1+flow+turbid+temp+estfish_bsmt_1
       pcope~hcope_1+pcope_1+mysid_1+potam_1+flow+turbid+temp+estfish_bsmt_1+rotif_m_1
       mysid~chla_1+hcope_1+pcope_1+amphi_m_1+mysid_1+flow+turbid+temp+estfish_bsmt_1
       estfish_bsmt~estfish_bsmt_1+hcope_1+pcope_1+amphi_m_1+rotif_m_1+mysid_1+flow+turbid+temp
'
modN='chla~chla_1+hcope_1+amphi_m_1+rotif_m_1+corbic_1+flow+turbid+temp
       hcope~chla_1+hcope_1+pcope_1+mysid_1+corbic_1+flow+turbid+temp+estfish_bsmt_1
       amphi_m~chla_1+amphi_m_1+flow+turbid+temp+estfish_bsmt_1
       rotif_m~chla_1+rotif_m_1+flow+turbid+temp+estfish_bsmt_1
       pcope~hcope_1+pcope_1+mysid_1+corbic_1+flow+turbid+temp+estfish_bsmt_1+chla_1
       mysid~hcope_1+pcope_1+mysid_1+amphi_m_1+flow+turbid+temp+estfish_bsmt_1
       estfish_bsmt~estfish_bsmt_1+hcope_1+pcope_1+amphi_m_1+rotif_m_1+mysid_1+flow+turbid+temp
'
modS='chla~chla_1+hcope_1+clad_1+rotif_m_1+corbic_1+flow+turbid+temp
       hcope~chla_1+hcope_1+pcope_1+corbic_1+flow+turbid+temp+estfish_bsmt_1
       clad~chla_1+clad_1+pcope_1+flow+turbid+temp+estfish_bsmt_1
       amphi_m~chla_1+amphi_m_1+flow+turbid+temp+estfish_bsmt_1
       rotif_m~chla_1+rotif_m_1+flow+turbid+temp+estfish_bsmt_1
       pcope~chla_1+hcope_1+clad_1+pcope_1+corbic_1+flow+turbid+temp+estfish_bsmt_1
       estfish_bsmt~estfish_bsmt_1+hcope_1+pcope_1+amphi_m_1+rotif_m_1+clad_1+flow+turbid+temp
'
modfitFW=sem(modFW, data=filter(fdr_ds,region=="Far West"))
modfitW=sem(modW, data=filter(fdr_ds,region=="West"))
modfitN=sem(modN, data=filter(fdr_ds,region=="North"))
modfitS=sem(modS, data=filter(fdr_ds,region=="South"))
summary(modfitFW, standardized=T, rsq=T)
## lavaan 0.6-10 ended normally after 29 iterations
## 
##   Estimator                                         ML
##   Optimization method                           NLMINB
##   Number of model parameters                        64
##                                                       
##                                                   Used       Total
##   Number of observations                           183         312
##                                                                   
## Model Test User Model:
##                                                       
##   Test statistic                                24.227
##   Degrees of freedom                                17
##   P-value (Chi-square)                           0.113
## 
## Parameter Estimates:
## 
##   Standard errors                             Standard
##   Information                                 Expected
##   Information saturated (h1) model          Structured
## 
## Regressions:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##   chla ~                                                                
##     chla_1            0.225    0.068    3.311    0.001    0.225    0.233
##     hcope_1           0.089    0.056    1.593    0.111    0.089    0.113
##     amphi_m_1        -0.011    0.067   -0.162    0.871   -0.011   -0.014
##     rotif_m_1        -0.096    0.064   -1.503    0.133   -0.096   -0.112
##     potam_1          -0.000    0.050   -0.009    0.993   -0.000   -0.001
##     flow              0.104    0.073    1.421    0.155    0.104    0.124
##     turbid           -0.102    0.072   -1.423    0.155   -0.102   -0.114
##     temp              0.106    0.063    1.685    0.092    0.106    0.124
##   hcope ~                                                               
##     chla_1            0.124    0.082    1.509    0.131    0.124    0.101
##     hcope_1           0.231    0.072    3.209    0.001    0.231    0.232
##     pcope_1           0.059    0.074    0.798    0.425    0.059    0.057
##     potam_1          -0.131    0.064   -2.057    0.040   -0.131   -0.144
##     flow             -0.063    0.084   -0.749    0.454   -0.063   -0.059
##     turbid           -0.049    0.088   -0.556    0.578   -0.049   -0.043
##     temp             -0.068    0.080   -0.857    0.391   -0.068   -0.063
##     estfish_bsmt_1   -0.137    0.080   -1.727    0.084   -0.137   -0.132
##   amphi_m ~                                                             
##     chla_1            0.052    0.040    1.307    0.191    0.052    0.043
##     amphi_m_1         0.732    0.039   18.979    0.000    0.732    0.748
##     flow             -0.265    0.043   -6.179    0.000   -0.265   -0.254
##     turbid            0.004    0.042    0.084    0.933    0.004    0.003
##     temp              0.017    0.037    0.451    0.652    0.017    0.016
##     estfish_bsmt_1    0.049    0.036    1.357    0.175    0.049    0.048
##   rotif_m ~                                                             
##     chla_1           -0.201    0.077   -2.600    0.009   -0.201   -0.177
##     rotif_m_1         0.344    0.068    5.045    0.000    0.344    0.345
##     flow              0.066    0.076    0.866    0.387    0.066    0.067
##     turbid            0.055    0.081    0.688    0.492    0.055    0.053
##     temp              0.025    0.072    0.348    0.728    0.025    0.025
##     estfish_bsmt_1   -0.016    0.069   -0.239    0.811   -0.016   -0.017
##   pcope ~                                                               
##     hcope_1           0.047    0.066    0.708    0.479    0.047    0.050
##     pcope_1           0.272    0.068    3.986    0.000    0.272    0.279
##     potam_1          -0.082    0.058   -1.407    0.159   -0.082   -0.096
##     flow              0.204    0.077    2.665    0.008    0.204    0.205
##     turbid            0.092    0.081    1.137    0.256    0.092    0.086
##     temp              0.150    0.073    2.061    0.039    0.150    0.147
##     estfish_bsmt_1   -0.046    0.073   -0.637    0.524   -0.046   -0.048
##   estfish_bsmt ~                                                        
##     estfish_bsmt_1    0.350    0.064    5.423    0.000    0.350    0.357
##     hcope_1          -0.090    0.058   -1.551    0.121   -0.090   -0.096
##     pcope_1           0.129    0.060    2.140    0.032    0.129    0.132
##     amphi_m_1        -0.055    0.069   -0.798    0.425   -0.055   -0.059
##     rotif_m_1        -0.148    0.063   -2.335    0.020   -0.148   -0.144
##     flow              0.085    0.074    1.154    0.248    0.085    0.085
##     turbid            0.234    0.072    3.238    0.001    0.234    0.218
##     temp             -0.064    0.065   -0.996    0.319   -0.064   -0.063
## 
## Covariances:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##  .chla ~~                                                               
##    .hcope             0.031    0.055    0.563    0.573    0.031    0.042
##    .amphi_m           0.012    0.026    0.471    0.638    0.012    0.035
##    .rotif_m           0.099    0.051    1.949    0.051    0.099    0.146
##    .pcope            -0.007    0.051   -0.138    0.890   -0.007   -0.010
##    .estfish_bsmt     -0.046    0.045   -1.025    0.306   -0.046   -0.076
##  .hcope ~~                                                              
##    .amphi_m          -0.010    0.032   -0.297    0.767   -0.010   -0.022
##    .rotif_m           0.068    0.063    1.071    0.284    0.068    0.079
##    .pcope            -0.205    0.065   -3.147    0.002   -0.205   -0.239
##    .estfish_bsmt     -0.064    0.056   -1.144    0.253   -0.064   -0.085
##  .amphi_m ~~                                                            
##    .rotif_m          -0.038    0.030   -1.281    0.200   -0.038   -0.095
##    .pcope            -0.003    0.030   -0.099    0.921   -0.003   -0.007
##    .estfish_bsmt     -0.015    0.026   -0.567    0.571   -0.015   -0.042
##  .rotif_m ~~                                                            
##    .pcope             0.033    0.058    0.574    0.566    0.033    0.042
##    .estfish_bsmt     -0.049    0.051   -0.954    0.340   -0.049   -0.071
##  .pcope ~~                                                              
##    .estfish_bsmt     -0.063    0.051   -1.222    0.222   -0.063   -0.091
## 
## Variances:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##    .chla              0.596    0.062    9.566    0.000    0.596    0.883
##    .hcope             0.935    0.098    9.566    0.000    0.935    0.852
##    .amphi_m           0.204    0.021    9.566    0.000    0.204    0.192
##    .rotif_m           0.776    0.081    9.566    0.000    0.776    0.839
##    .pcope             0.786    0.082    9.566    0.000    0.786    0.813
##    .estfish_bsmt      0.608    0.064    9.566    0.000    0.608    0.624
## 
## R-Square:
##                    Estimate
##     chla              0.117
##     hcope             0.148
##     amphi_m           0.808
##     rotif_m           0.161
##     pcope             0.187
##     estfish_bsmt      0.376
summary(modfitW, standardized=T, rsq=T)
## lavaan 0.6-10 ended normally after 27 iterations
## 
##   Estimator                                         ML
##   Optimization method                           NLMINB
##   Number of model parameters                        87
##                                                       
##                                                   Used       Total
##   Number of observations                           202         312
##                                                                   
## Model Test User Model:
##                                                       
##   Test statistic                                24.239
##   Degrees of freedom                                18
##   P-value (Chi-square)                           0.147
## 
## Parameter Estimates:
## 
##   Standard errors                             Standard
##   Information                                 Expected
##   Information saturated (h1) model          Structured
## 
## Regressions:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##   chla ~                                                                
##     chla_1            0.172    0.069    2.495    0.013    0.172    0.176
##     hcope_1           0.019    0.068    0.284    0.776    0.019    0.020
##     amphi_m_1         0.125    0.067    1.874    0.061    0.125    0.141
##     rotif_m_1         0.096    0.063    1.543    0.123    0.096    0.112
##     potam_1          -0.039    0.070   -0.557    0.578   -0.039   -0.042
##     flow              0.055    0.069    0.791    0.429    0.055    0.059
##     turbid            0.082    0.071    1.157    0.247    0.082    0.087
##     temp             -0.094    0.061   -1.545    0.122   -0.094   -0.106
##     mysid_1          -0.134    0.068   -1.979    0.048   -0.134   -0.144
##   hcope ~                                                               
##     chla_1            0.044    0.071    0.628    0.530    0.044    0.042
##     hcope_1           0.281    0.070    3.987    0.000    0.281    0.275
##     pcope_1          -0.111    0.063   -1.764    0.078   -0.111   -0.116
##     mysid_1           0.078    0.073    1.078    0.281    0.078    0.078
##     potam_1          -0.176    0.068   -2.599    0.009   -0.176   -0.176
##     flow             -0.140    0.072   -1.943    0.052   -0.140   -0.139
##     turbid           -0.107    0.074   -1.452    0.147   -0.107   -0.106
##     temp              0.080    0.063    1.269    0.204    0.080    0.084
##     estfish_bsmt_1    0.043    0.064    0.670    0.503    0.043    0.044
##     rotif_m_1         0.213    0.061    3.489    0.000    0.213    0.230
##   amphi_m ~                                                             
##     chla_1           -0.045    0.042   -1.076    0.282   -0.045   -0.041
##     amphi_m_1         0.778    0.040   19.473    0.000    0.778    0.777
##     mysid_1           0.078    0.041    1.936    0.053    0.078    0.075
##     flow              0.003    0.041    0.076    0.940    0.003    0.003
##     turbid           -0.106    0.043   -2.450    0.014   -0.106   -0.101
##     temp             -0.101    0.038   -2.649    0.008   -0.101   -0.101
##     estfish_bsmt_1   -0.184    0.040   -4.577    0.000   -0.184   -0.180
##   rotif_m ~                                                             
##     chla_1            0.032    0.067    0.478    0.632    0.032    0.028
##     rotif_m_1         0.457    0.060    7.666    0.000    0.457    0.450
##     flow              0.215    0.067    3.197    0.001    0.215    0.195
##     turbid           -0.156    0.067   -2.338    0.019   -0.156   -0.141
##     temp             -0.018    0.060   -0.291    0.771   -0.018   -0.017
##     estfish_bsmt_1   -0.199    0.061   -3.261    0.001   -0.199   -0.185
##   pcope ~                                                               
##     hcope_1          -0.163    0.062   -2.642    0.008   -0.163   -0.154
##     pcope_1           0.432    0.057    7.551    0.000    0.432    0.436
##     mysid_1           0.141    0.065    2.182    0.029    0.141    0.135
##     potam_1           0.047    0.063    0.747    0.455    0.047    0.045
##     flow              0.156    0.064    2.452    0.014    0.156    0.150
##     turbid           -0.132    0.066   -2.002    0.045   -0.132   -0.125
##     temp              0.220    0.056    3.948    0.000    0.220    0.222
##     estfish_bsmt_1    0.021    0.059    0.364    0.716    0.021    0.021
##     rotif_m_1         0.131    0.055    2.354    0.019    0.131    0.136
##   mysid ~                                                               
##     chla_1            0.174    0.062    2.794    0.005    0.174    0.167
##     hcope_1           0.049    0.062    0.790    0.429    0.049    0.049
##     pcope_1           0.093    0.056    1.661    0.097    0.093    0.099
##     amphi_m_1        -0.113    0.059   -1.926    0.054   -0.113   -0.118
##     mysid_1           0.372    0.065    5.730    0.000    0.372    0.373
##     flow             -0.163    0.061   -2.661    0.008   -0.163   -0.164
##     turbid            0.250    0.066    3.788    0.000    0.250    0.249
##     temp              0.109    0.057    1.926    0.054    0.109    0.115
##     estfish_bsmt_1    0.003    0.059    0.053    0.957    0.003    0.003
##   estfish_bsmt ~                                                        
##     estfish_bsmt_1    0.230    0.071    3.240    0.001    0.230    0.223
##     hcope_1           0.109    0.073    1.494    0.135    0.109    0.102
##     pcope_1          -0.008    0.069   -0.120    0.904   -0.008   -0.008
##     amphi_m_1        -0.193    0.075   -2.588    0.010   -0.193   -0.191
##     rotif_m_1         0.032    0.069    0.467    0.640    0.032    0.033
##     mysid_1          -0.089    0.077   -1.148    0.251   -0.089   -0.084
##     flow             -0.206    0.074   -2.792    0.005   -0.206   -0.195
##     turbid            0.205    0.078    2.610    0.009    0.205    0.192
##     temp              0.019    0.066    0.283    0.777    0.019    0.019
## 
## Covariances:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##  .chla ~~                                                               
##    .hcope             0.153    0.052    2.952    0.003    0.153    0.212
##    .amphi_m          -0.016    0.031   -0.507    0.612   -0.016   -0.036
##    .rotif_m           0.054    0.049    1.101    0.271    0.054    0.078
##    .pcope             0.012    0.045    0.264    0.791    0.012    0.019
##    .mysid             0.079    0.046    1.730    0.084    0.079    0.123
##    .estfish_bsmt      0.061    0.054    1.125    0.261    0.061    0.079
##  .hcope ~~                                                              
##    .amphi_m          -0.057    0.032   -1.762    0.078   -0.057   -0.125
##    .rotif_m          -0.013    0.051   -0.264    0.792   -0.013   -0.019
##    .pcope             0.069    0.047    1.450    0.147    0.069    0.103
##    .mysid             0.202    0.049    4.085    0.000    0.202    0.300
##    .estfish_bsmt     -0.035    0.056   -0.628    0.530   -0.035   -0.044
##  .amphi_m ~~                                                            
##    .rotif_m           0.057    0.031    1.832    0.067    0.057    0.130
##    .pcope             0.050    0.029    1.751    0.080    0.050    0.124
##    .mysid            -0.046    0.029   -1.598    0.110   -0.046   -0.113
##    .estfish_bsmt     -0.020    0.034   -0.589    0.556   -0.020   -0.041
##  .rotif_m ~~                                                            
##    .pcope             0.031    0.045    0.673    0.501    0.031    0.047
##    .mysid             0.039    0.046    0.847    0.397    0.039    0.060
##    .estfish_bsmt     -0.025    0.054   -0.470    0.639   -0.025   -0.033
##  .pcope ~~                                                              
##    .mysid             0.069    0.042    1.617    0.106    0.069    0.115
##    .estfish_bsmt      0.021    0.050    0.416    0.677    0.021    0.029
##  .mysid ~~                                                              
##    .estfish_bsmt      0.115    0.051    2.251    0.024    0.115    0.160
## 
## Variances:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##    .chla              0.695    0.069   10.050    0.000    0.695    0.848
##    .hcope             0.750    0.075   10.050    0.000    0.750    0.786
##    .amphi_m           0.273    0.027   10.050    0.000    0.273    0.265
##    .rotif_m           0.699    0.070   10.050    0.000    0.699    0.608
##    .pcope             0.596    0.059   10.050    0.000    0.596    0.580
##    .mysid             0.602    0.060   10.050    0.000    0.602    0.644
##    .estfish_bsmt      0.848    0.084   10.050    0.000    0.848    0.803
## 
## R-Square:
##                    Estimate
##     chla              0.152
##     hcope             0.214
##     amphi_m           0.735
##     rotif_m           0.392
##     pcope             0.420
##     mysid             0.356
##     estfish_bsmt      0.197
summary(modfitN, standardized=T, rsq=T)
## lavaan 0.6-10 ended normally after 31 iterations
## 
##   Estimator                                         ML
##   Optimization method                           NLMINB
##   Number of model parameters                        83
##                                                       
##                                                   Used       Total
##   Number of observations                           186         312
##                                                                   
## Model Test User Model:
##                                                       
##   Test statistic                                30.817
##   Degrees of freedom                                22
##   P-value (Chi-square)                           0.100
## 
## Parameter Estimates:
## 
##   Standard errors                             Standard
##   Information                                 Expected
##   Information saturated (h1) model          Structured
## 
## Regressions:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##   chla ~                                                                
##     chla_1            0.200    0.074    2.700    0.007    0.200    0.193
##     hcope_1          -0.044    0.094   -0.464    0.642   -0.044   -0.037
##     amphi_m_1         0.023    0.074    0.312    0.755    0.023    0.022
##     rotif_m_1        -0.003    0.072   -0.042    0.967   -0.003   -0.003
##     corbic_1         -0.047    0.070   -0.672    0.501   -0.047   -0.049
##     flow              0.018    0.075    0.244    0.808    0.018    0.019
##     turbid            0.084    0.070    1.207    0.228    0.084    0.090
##     temp              0.145    0.069    2.098    0.036    0.145    0.156
##   hcope ~                                                               
##     chla_1           -0.020    0.046   -0.427    0.669   -0.020   -0.023
##     hcope_1           0.166    0.074    2.246    0.025    0.166    0.168
##     pcope_1          -0.108    0.046   -2.321    0.020   -0.108   -0.143
##     mysid_1           0.049    0.063    0.778    0.436    0.049    0.060
##     corbic_1          0.126    0.043    2.904    0.004    0.126    0.155
##     flow             -0.380    0.051   -7.428    0.000   -0.380   -0.479
##     turbid            0.080    0.049    1.616    0.106    0.080    0.102
##     temp              0.094    0.046    2.048    0.041    0.094    0.121
##     estfish_bsmt_1    0.003    0.047    0.070    0.944    0.003    0.004
##   amphi_m ~                                                             
##     chla_1            0.060    0.062    0.979    0.328    0.060    0.060
##     amphi_m_1         0.522    0.061    8.488    0.000    0.522    0.525
##     flow              0.037    0.063    0.590    0.555    0.037    0.041
##     turbid           -0.038    0.058   -0.649    0.516   -0.038   -0.042
##     temp             -0.038    0.057   -0.672    0.502   -0.038   -0.043
##     estfish_bsmt_1   -0.064    0.058   -1.107    0.268   -0.064   -0.075
##   rotif_m ~                                                             
##     chla_1           -0.115    0.069   -1.665    0.096   -0.115   -0.102
##     rotif_m_1         0.138    0.067    2.067    0.039    0.138    0.134
##     flow              0.519    0.071    7.347    0.000    0.519    0.504
##     turbid           -0.083    0.064   -1.296    0.195   -0.083   -0.082
##     temp             -0.036    0.063   -0.573    0.567   -0.036   -0.036
##     estfish_bsmt_1    0.017    0.064    0.273    0.784    0.017    0.018
##   pcope ~                                                               
##     hcope_1          -0.042    0.111   -0.381    0.703   -0.042   -0.032
##     pcope_1           0.270    0.070    3.882    0.000    0.270    0.267
##     mysid_1           0.130    0.094    1.390    0.165    0.130    0.119
##     corbic_1          0.039    0.069    0.569    0.570    0.039    0.036
##     flow             -0.207    0.078   -2.650    0.008   -0.207   -0.194
##     turbid           -0.260    0.075   -3.466    0.001   -0.260   -0.247
##     temp              0.048    0.070    0.681    0.496    0.048    0.046
##     estfish_bsmt_1   -0.102    0.071   -1.437    0.151   -0.102   -0.103
##     chla_1            0.189    0.075    2.513    0.012    0.189    0.163
##   mysid ~                                                               
##     hcope_1           0.056    0.089    0.629    0.529    0.056    0.047
##     pcope_1          -0.055    0.056   -0.992    0.321   -0.055   -0.061
##     mysid_1           0.205    0.075    2.747    0.006    0.205    0.208
##     amphi_m_1        -0.090    0.056   -1.619    0.105   -0.090   -0.086
##     flow             -0.389    0.062   -6.271    0.000   -0.389   -0.405
##     turbid            0.216    0.060    3.613    0.000    0.216    0.227
##     temp              0.069    0.055    1.258    0.208    0.069    0.074
##     estfish_bsmt_1    0.045    0.057    0.792    0.428    0.045    0.050
##   estfish_bsmt ~                                                        
##     estfish_bsmt_1    0.140    0.072    1.935    0.053    0.140    0.139
##     hcope_1           0.151    0.113    1.335    0.182    0.151    0.112
##     pcope_1          -0.055    0.071   -0.772    0.440   -0.055   -0.053
##     amphi_m_1        -0.044    0.076   -0.577    0.564   -0.044   -0.037
##     rotif_m_1         0.133    0.074    1.801    0.072    0.133    0.123
##     mysid_1           0.129    0.095    1.358    0.174    0.129    0.116
##     flow             -0.402    0.079   -5.070    0.000   -0.402   -0.371
##     turbid            0.085    0.075    1.120    0.263    0.085    0.079
##     temp             -0.052    0.069   -0.753    0.451   -0.052   -0.050
## 
## Covariances:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##  .chla ~~                                                               
##    .hcope             0.033    0.040    0.815    0.415    0.033    0.060
##    .amphi_m          -0.016    0.051   -0.320    0.749   -0.016   -0.023
##    .rotif_m           0.098    0.057    1.718    0.086    0.098    0.127
##    .pcope            -0.106    0.062   -1.715    0.086   -0.106   -0.127
##    .mysid             0.069    0.049    1.390    0.164    0.069    0.102
##    .estfish_bsmt      0.013    0.062    0.208    0.835    0.013    0.015
##  .hcope ~~                                                              
##    .amphi_m           0.036    0.034    1.067    0.286    0.036    0.079
##    .rotif_m           0.002    0.038    0.063    0.949    0.002    0.005
##    .pcope             0.068    0.041    1.657    0.098    0.068    0.122
##    .mysid             0.170    0.035    4.883    0.000    0.170    0.383
##    .estfish_bsmt     -0.011    0.041   -0.280    0.779   -0.011   -0.021
##  .amphi_m ~~                                                            
##    .rotif_m           0.029    0.048    0.599    0.549    0.029    0.044
##    .pcope            -0.122    0.053   -2.320    0.020   -0.122   -0.173
##    .mysid             0.069    0.042    1.670    0.095    0.069    0.123
##    .estfish_bsmt      0.085    0.052    1.614    0.107    0.085    0.119
##  .rotif_m ~~                                                            
##    .pcope             0.029    0.058    0.504    0.614    0.029    0.037
##    .mysid             0.009    0.046    0.198    0.843    0.009    0.015
##    .estfish_bsmt     -0.014    0.058   -0.243    0.808   -0.014   -0.018
##  .pcope ~~                                                              
##    .mysid             0.104    0.050    2.063    0.039    0.104    0.153
##    .estfish_bsmt      0.037    0.063    0.589    0.556    0.037    0.043
##  .mysid ~~                                                              
##    .estfish_bsmt      0.049    0.050    0.987    0.324    0.049    0.073
## 
## Variances:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##    .chla              0.830    0.086    9.644    0.000    0.830    0.921
##    .hcope             0.365    0.038    9.644    0.000    0.365    0.583
##    .amphi_m           0.589    0.061    9.644    0.000    0.589    0.709
##    .rotif_m           0.723    0.075    9.644    0.000    0.723    0.682
##    .pcope             0.850    0.088    9.644    0.000    0.850    0.754
##    .mysid             0.538    0.056    9.644    0.000    0.538    0.584
##    .estfish_bsmt      0.855    0.089    9.644    0.000    0.855    0.732
## 
## R-Square:
##                    Estimate
##     chla              0.079
##     hcope             0.417
##     amphi_m           0.291
##     rotif_m           0.318
##     pcope             0.246
##     mysid             0.416
##     estfish_bsmt      0.268
summary(modfitS, standardized=T, rsq=T)
## lavaan 0.6-10 ended normally after 20 iterations
## 
##   Estimator                                         ML
##   Optimization method                           NLMINB
##   Number of model parameters                        81
##                                                       
##                                                   Used       Total
##   Number of observations                           192         312
##                                                                   
## Model Test User Model:
##                                                       
##   Test statistic                                27.447
##   Degrees of freedom                                24
##   P-value (Chi-square)                           0.284
## 
## Parameter Estimates:
## 
##   Standard errors                             Standard
##   Information                                 Expected
##   Information saturated (h1) model          Structured
## 
## Regressions:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##   chla ~                                                                
##     chla_1            0.182    0.073    2.502    0.012    0.182    0.177
##     hcope_1           0.075    0.069    1.094    0.274    0.075    0.074
##     clad_1            0.233    0.067    3.460    0.001    0.233    0.244
##     rotif_m_1        -0.089    0.068   -1.314    0.189   -0.089   -0.088
##     corbic_1         -0.044    0.067   -0.654    0.513   -0.044   -0.043
##     flow             -0.117    0.074   -1.578    0.115   -0.117   -0.112
##     turbid            0.016    0.067    0.239    0.811    0.016    0.016
##     temp              0.081    0.065    1.235    0.217    0.081    0.083
##   hcope ~                                                               
##     chla_1            0.178    0.062    2.894    0.004    0.178    0.177
##     hcope_1           0.352    0.063    5.598    0.000    0.352    0.353
##     pcope_1           0.033    0.060    0.540    0.589    0.033    0.034
##     corbic_1          0.100    0.061    1.635    0.102    0.100    0.101
##     flow             -0.154    0.065   -2.372    0.018   -0.154   -0.150
##     turbid           -0.096    0.060   -1.587    0.112   -0.096   -0.099
##     temp              0.164    0.059    2.767    0.006    0.164    0.172
##     estfish_bsmt_1   -0.175    0.060   -2.917    0.004   -0.175   -0.183
##   clad ~                                                                
##     chla_1            0.210    0.062    3.400    0.001    0.210    0.194
##     clad_1            0.518    0.058    8.870    0.000    0.518    0.516
##     pcope_1          -0.019    0.057   -0.329    0.742   -0.019   -0.018
##     flow              0.211    0.062    3.431    0.001    0.211    0.192
##     turbid           -0.038    0.058   -0.658    0.510   -0.038   -0.037
##     temp              0.105    0.057    1.831    0.067    0.105    0.102
##     estfish_bsmt_1   -0.088    0.056   -1.571    0.116   -0.088   -0.086
##   amphi_m ~                                                             
##     chla_1           -0.052    0.074   -0.699    0.484   -0.052   -0.047
##     amphi_m_1         0.234    0.069    3.395    0.001    0.234    0.235
##     flow             -0.052    0.077   -0.676    0.499   -0.052   -0.047
##     turbid            0.201    0.074    2.730    0.006    0.201    0.193
##     temp              0.100    0.072    1.399    0.162    0.100    0.097
##     estfish_bsmt_1    0.057    0.072    0.784    0.433    0.057    0.055
##   rotif_m ~                                                             
##     chla_1           -0.031    0.069   -0.442    0.659   -0.031   -0.030
##     rotif_m_1         0.196    0.067    2.921    0.003    0.196    0.194
##     flow              0.315    0.071    4.433    0.000    0.315    0.303
##     turbid           -0.079    0.066   -1.193    0.233   -0.079   -0.081
##     temp             -0.036    0.066   -0.548    0.584   -0.036   -0.037
##     estfish_bsmt_1    0.117    0.066    1.770    0.077    0.117    0.120
##   pcope ~                                                               
##     chla_1            0.271    0.069    3.922    0.000    0.271    0.249
##     hcope_1          -0.064    0.067   -0.949    0.343   -0.064   -0.059
##     clad_1            0.073    0.066    1.114    0.265    0.073    0.072
##     pcope_1           0.476    0.065    7.308    0.000    0.476    0.458
##     corbic_1         -0.028    0.064   -0.444    0.657   -0.028   -0.027
##     flow              0.008    0.072    0.109    0.913    0.008    0.007
##     turbid           -0.068    0.066   -1.033    0.302   -0.068   -0.065
##     temp              0.003    0.065    0.047    0.962    0.003    0.003
##     estfish_bsmt_1   -0.056    0.065   -0.854    0.393   -0.056   -0.054
##   estfish_bsmt ~                                                        
##     estfish_bsmt_1    0.220    0.068    3.254    0.001    0.220    0.226
##     hcope_1          -0.005    0.071   -0.073    0.942   -0.005   -0.005
##     pcope_1          -0.067    0.069   -0.969    0.333   -0.067   -0.068
##     amphi_m_1         0.115    0.064    1.787    0.074    0.115    0.123
##     rotif_m_1        -0.008    0.069   -0.121    0.904   -0.008   -0.008
##     clad_1            0.131    0.067    1.950    0.051    0.131    0.137
##     flow             -0.106    0.074   -1.430    0.153   -0.106   -0.102
##     turbid            0.218    0.069    3.160    0.002    0.218    0.221
##     temp             -0.003    0.067   -0.048    0.962   -0.003   -0.003
## 
## Covariances:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##  .chla ~~                                                               
##    .hcope             0.059    0.053    1.124    0.261    0.059    0.081
##    .clad              0.159    0.052    3.046    0.002    0.159    0.225
##    .amphi_m           0.006    0.064    0.101    0.920    0.006    0.007
##    .rotif_m           0.146    0.060    2.426    0.015    0.146    0.178
##    .pcope            -0.041    0.057   -0.713    0.476   -0.041   -0.052
##    .estfish_bsmt     -0.012    0.059   -0.201    0.841   -0.012   -0.014
##  .hcope ~~                                                              
##    .clad              0.037    0.045    0.827    0.408    0.037    0.060
##    .amphi_m           0.014    0.057    0.253    0.800    0.014    0.018
##    .rotif_m           0.007    0.053    0.125    0.901    0.007    0.009
##    .pcope             0.008    0.051    0.159    0.874    0.008    0.011
##    .estfish_bsmt     -0.008    0.053   -0.152    0.879   -0.008   -0.011
##  .clad ~~                                                               
##    .amphi_m          -0.082    0.055   -1.492    0.136   -0.082   -0.108
##    .rotif_m           0.072    0.051    1.418    0.156    0.072    0.103
##    .pcope             0.077    0.049    1.563    0.118    0.077    0.114
##    .estfish_bsmt      0.034    0.051    0.665    0.506    0.034    0.048
##  .amphi_m ~~                                                            
##    .rotif_m           0.029    0.064    0.458    0.647    0.029    0.033
##    .pcope             0.030    0.062    0.493    0.622    0.030    0.036
##    .estfish_bsmt     -0.072    0.064   -1.125    0.261   -0.072   -0.081
##  .rotif_m ~~                                                            
##    .pcope             0.153    0.058    2.627    0.009    0.153    0.193
##    .estfish_bsmt     -0.013    0.059   -0.212    0.832   -0.013   -0.015
##  .pcope ~~                                                              
##    .estfish_bsmt      0.117    0.058    2.032    0.042    0.117    0.148
## 
## Variances:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##    .chla              0.824    0.084    9.798    0.000    0.824    0.850
##    .hcope             0.648    0.066    9.798    0.000    0.648    0.695
##    .clad              0.601    0.061    9.798    0.000    0.601    0.560
##    .amphi_m           0.958    0.098    9.798    0.000    0.958    0.872
##    .rotif_m           0.820    0.084    9.798    0.000    0.820    0.851
##    .pcope             0.762    0.078    9.798    0.000    0.762    0.701
##    .estfish_bsmt      0.817    0.083    9.798    0.000    0.817    0.839
## 
## R-Square:
##                    Estimate
##     chla              0.150
##     hcope             0.305
##     clad              0.440
##     amphi_m           0.128
##     rotif_m           0.149
##     pcope             0.299
##     estfish_bsmt      0.161
#modificationindices(modfitW, sort=T, maximum.number=20)
#residuals(modfitW)

labelsfarwest=createLabels(modfitFW, cnameslag)
labelswest=createLabels(modfitW, cnameslag)
labelsnorth=createLabels(modfitN, cnameslag)
labelssouth=createLabels(modfitS, cnameslag)

#FAR WEST
# myLavaanPlot(model=modfitFW, labels=labelsfarwest,
#                        node_options=list(shape="box", fontname="Helvetica"), 
#                        coefs=TRUE, stand=TRUE, covs=FALSE, sig=0.05, 
#                        width=c("regress","latent"),
#                        color=c("regress","latent"))

zoop_plot_far_west <- createGraph(fit=modfitFW, 
                                  reference_df=cnameslag, 
                                  model_type="monthly_zoop",
                                  region="Far West",
                                  title="Far West",
                                  manual_port_settings=TRUE)
zoop_plot_far_west
#WEST
# myLavaanPlot(model=modfitW, labels=labelswest,
#                        node_options=list(shape="box", fontname="Helvetica"), 
#                        coefs=TRUE, stand=TRUE, covs=FALSE, sig=0.05, 
#                        width=c("regress","latent"),
#                        color=c("regress","latent"))

zoop_plot_west <- createGraph(fit=modfitW, 
                              reference_df=cnameslag, 
                              model_type="monthly_zoop",
                              region="West",
                              title="West",
                              manual_port_settings=TRUE)
zoop_plot_west
#NORTH
# myLavaanPlot(model=modfitN, labels=labelsnorth,
#                        node_options=list(shape="box", fontname="Helvetica"), 
#                        coefs=TRUE, stand=TRUE, covs=FALSE, sig=0.05, 
#                        width=c("regress","latent"),
#                        color=c("regress","latent"))

zoop_plot_north <- createGraph(fit=modfitN, 
                               reference_df=cnameslag, 
                               model_type="monthly_zoop",
                               region="North",
                               title="North",
                               manual_port_settings=TRUE)
zoop_plot_north
#SOUTH
# myLavaanPlot(model=modfitS, labels=labelssouth,
#                        node_options=list(shape="box", fontname="Helvetica"), 
#                        coefs=TRUE, stand=TRUE, covs=FALSE, sig=0.05, 
#                        width=c("regress","latent"),
#                        color=c("regress","latent"))

zoop_plot_south <- createGraph(fit=modfitS, 
                               reference_df=cnameslag, 
                               model_type="monthly_zoop",
                               region="South",
                               title="South",
                               manual_port_settings=TRUE)
zoop_plot_south

Save updated SEM diagrams

zoop_grobs <-  map(list(zoop_plot_far_west,
                        zoop_plot_west,
                        zoop_plot_north,
                        zoop_plot_south), ~convert_html_to_grob(.x, 2000))
zoop_figure <- ggarrange(plotlist=zoop_grobs, labels="auto",
                         font.label=list(size=11)) %>%
  annotate_figure(top = text_grob("Monthly Regional Models (zooplankton groups)",
                                  color = "black",
                                  face = "bold",
                                  size = 11))

ggsave('./fig_output/sem_zoop.png',zoop_figure, width=8, height=7, dpi=300, bg = "white")

Total effects

Haven’t done yet.

Growth rates

Upper trophic

modFW='hzoop_gr~hb1*chla_1+hs1*hzoop_1+ht1*pzoop_1+ht2*potam_1+ht3*estfish_bsmt_1+ha1*flow+ha2*temp+ha3*turbid
        pzoop_gr~pb1*hzoop_1+ps1*pzoop_1+pt1*potam_1+pt2*estfish_bsmt_1+pa1*flow+pa2*temp+pa3*turbid
        estfish_bsmt_gr~fb1*hzoop_1+fb2*pzoop_1+fs1*estfish_bsmt_1+fa1*flow+fa2*temp+fa3*turbid+ft1*marfish_bsmt_1+ft2*sbass1_bsmt_1
        
        hb:=sqrt(hb1^2)
        hs:=sqrt(hs1^2)
        ht:=sqrt(ht1^2+ht2^2+ht3^2)
        ha:=sqrt(ha1^2+ha2^2+ha3^2)
        
        pb:=sqrt(pb1^2)
        ps:=sqrt(ps1^2)
        pt:=sqrt(pt1^2+pt2^2)
        pa:=sqrt(pa1^2+pa2^2+pa3^2)
        
        fb:=sqrt(fb1^2+fb2^2)
        fs:=sqrt(fs1^2)
        ft:=sqrt(ft1^2+ft2^2)
        fa:=sqrt(fa1^2+fa2^2+fa3^2)
'

modW='hzoop_gr~hb1*chla_1+hs1*hzoop_1+ht1*pzoop_1+ht2*potam_1+ht3*estfish_bsmt_1+ha1*flow+ha2*temp+ha3*turbid
        pzoop_gr~pb1*chla_1+pb2*hzoop_1+ps1*pzoop_1+pt1*potam_1+pt2*estfish_bsmt_1+pa1*flow+pa2*temp+pa3*turbid
        estfish_bsmt_gr~fb1*hzoop_1+fb2*pzoop_1+fs1*estfish_bsmt_1+fa1*flow+fa2*temp+fa3*turbid+ft1*sbass1_bsmt_1
        
        hb:=sqrt(hb1^2)
        hs:=sqrt(hs1^2)
        ht:=sqrt(ht1^2+ht2^2+ht3^2)
        ha:=sqrt(ha1^2+ha2^2+ha3^2)
        
        pb:=sqrt(pb1^2+pb2^2)
        ps:=sqrt(ps1^2)
        pt:=sqrt(pt1^2+pt2^2)
        pa:=sqrt(pa1^2+pa2^2+pa3^2)
        
        fb:=sqrt(fb1^2+fb2^2)
        fs:=sqrt(fs1^2)
        ft:=sqrt(ft1^2)
        fa:=sqrt(fa1^2+fa2^2+fa3^2)
'

modN='hzoop_gr~hb1*chla_1+hs1*hzoop_1+ht1*pzoop_1+ht2*corbic_1+ht3*estfish_bsmt_1+ha1*flow+ha2*temp+ha3*turbid
        pzoop_gr~pb1*chla_1+pb2*hzoop_1+ps1*pzoop_1+pt1*corbic_1+pt2*estfish_bsmt_1+pa1*flow+pa2*temp+pa3*turbid
        estfish_bsmt_gr~fb1*hzoop_1+fb2*pzoop_1+fs1*estfish_bsmt_1+fa1*flow+fa2*temp+fa3*turbid+ft1*sside_1+ft2*cent_1+ft3*sbass1_bsmt_1
        
        hb:=sqrt(hb1^2)
        hs:=sqrt(hs1^2)
        ht:=sqrt(ht1^2+ht2^2+ht3^2)
        ha:=sqrt(ha1^2+ha2^2+ha3^2)
        
        pb:=sqrt(pb1^2+pb2^2)
        ps:=sqrt(ps1^2)
        pt:=sqrt(pt1^2+pt2^2)
        pa:=sqrt(pa1^2+pa2^2+pa3^2)
        
        fb:=sqrt(fb1^2+fb2^2)
        fs:=sqrt(fs1^2)
        ft:=sqrt(ft1^2+ft2^2+ft3^2)
        fa:=sqrt(fa1^2+fa2^2+fa3^2)
'

modS='hzoop_gr~hb1*chla_1+hs1*hzoop_1+ht1*pzoop_1+ht2*corbic_1+ht3*estfish_bsmt_1+ha1*flow+ha2*temp+ha3*turbid
        pzoop_gr~pb1*chla_1+pb2*hzoop_1+ps1*pzoop_1+pt1*corbic_1+pt2*estfish_bsmt_1+pa1*flow+pa2*temp+pa3*turbid
        estfish_bsmt_gr~fb1*chla_1+fb2*hzoop_1+fb3*pzoop_1+fs1*estfish_bsmt_1+fa1*flow+fa2*temp+fa3*turbid+ft1*sside_1+ft2*cent_1+ft3*sbass1_bsmt_1
        
        hb:=sqrt(hb1^2)
        hs:=sqrt(hs1^2)
        ht:=sqrt(ht1^2+ht2^2+ht3^2)
        ha:=sqrt(ha1^2+ha2^2+ha3^2)
        
        pb:=sqrt(pb1^2+pb2^2)
        ps:=sqrt(ps1^2)
        pt:=sqrt(pt1^2+pt2^2)
        pa:=sqrt(pa1^2+pa2^2+pa3^2)
        
        fb:=sqrt(fb1^2+fb2^2+fb3^2)
        fs:=sqrt(fs1^2)
        ft:=sqrt(ft1^2+ft2^2+ft3^2)
        fa:=sqrt(fa1^2+fa2^2+fa3^2)
'

modfitFW=sem(modFW, data=filter(fdr_ds,region=="Far West"))
modfitW=sem(modW, data=filter(fdr_ds,region=="West"))
modfitN=sem(modN, data=filter(fdr_ds,region=="North"))
modfitS=sem(modS, data=filter(fdr_ds,region=="South"))
summary(modfitFW, standardized=T, rsq=T)
## lavaan 0.6-10 ended normally after 24 iterations
## 
##   Estimator                                         ML
##   Optimization method                           NLMINB
##   Number of model parameters                        29
##                                                       
##                                                   Used       Total
##   Number of observations                           191         312
##                                                                   
## Model Test User Model:
##                                                       
##   Test statistic                                 6.547
##   Degrees of freedom                                 7
##   P-value (Chi-square)                           0.478
## 
## Parameter Estimates:
## 
##   Standard errors                             Standard
##   Information                                 Expected
##   Information saturated (h1) model          Structured
## 
## Regressions:
##                     Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##   hzoop_gr ~                                                             
##     chla_1   (hb1)     0.047    0.058    0.796    0.426    0.047    0.046
##     hzoop_1  (hs1)    -0.504    0.050  -10.079    0.000   -0.504   -0.618
##     pzoop_1  (ht1)     0.062    0.048    1.291    0.197    0.062    0.078
##     potam_1  (ht2)    -0.134    0.045   -2.990    0.003   -0.134   -0.178
##     estfs__1 (ht3)    -0.123    0.053   -2.304    0.021   -0.123   -0.145
##     flow     (ha1)    -0.047    0.058   -0.816    0.415   -0.047   -0.054
##     temp     (ha2)    -0.057    0.055   -1.027    0.304   -0.057   -0.064
##     turbid   (ha3)     0.052    0.062    0.844    0.399    0.052    0.056
##   pzoop_gr ~                                                             
##     hzoop_1  (pb1)     0.068    0.103    0.662    0.508    0.068    0.042
##     pzoop_1  (ps1)    -0.898    0.100   -9.013    0.000   -0.898   -0.567
##     potam_1  (pt1)    -0.181    0.092   -1.973    0.048   -0.181   -0.121
##     estfs__1 (pt2)     0.016    0.110    0.148    0.882    0.016    0.010
##     flow     (pa1)     0.119    0.120    0.990    0.322    0.119    0.068
##     temp     (pa2)    -0.013    0.115   -0.114    0.909   -0.013   -0.007
##     turbid   (pa3)     0.329    0.128    2.564    0.010    0.329    0.175
##   estfish_bsmt_gr ~                                                      
##     hzoop_1  (fb1)    -0.421    0.133   -3.170    0.002   -0.421   -0.193
##     pzoop_1  (fb2)     0.242    0.132    1.834    0.067    0.242    0.113
##     estfs__1 (fs1)    -1.370    0.151   -9.097    0.000   -1.370   -0.601
##     flow     (fa1)     0.171    0.160    1.069    0.285    0.171    0.073
##     temp     (fa2)    -0.033    0.153   -0.214    0.831   -0.033   -0.014
##     turbid   (fa3)     0.482    0.172    2.807    0.005    0.482    0.190
##     mrfsh__1 (ft1)    -0.032    0.150   -0.213    0.831   -0.032   -0.013
##     sbss1__1 (ft2)    -0.043    0.152   -0.285    0.776   -0.043   -0.018
## 
## Covariances:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##  .hzoop_gr ~~                                                           
##    .pzoop_gr         -0.080    0.069   -1.161    0.246   -0.080   -0.084
##    .estfsh_bsmt_gr   -0.046    0.090   -0.514    0.607   -0.046   -0.037
##  .pzoop_gr ~~                                                           
##    .estfsh_bsmt_gr   -0.401    0.189   -2.126    0.034   -0.401   -0.156
## 
## Variances:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##    .hzoop_gr          0.460    0.047    9.772    0.000    0.460    0.628
##    .pzoop_gr          1.974    0.202    9.772    0.000    1.974    0.685
##    .estfsh_bsmt_gr    3.366    0.344    9.772    0.000    3.366    0.641
## 
## R-Square:
##                    Estimate
##     hzoop_gr          0.372
##     pzoop_gr          0.315
##     estfsh_bsmt_gr    0.359
## 
## Defined Parameters:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##     hb                0.047    0.058    0.796    0.426    0.047    0.046
##     hs                0.504    0.050   10.079    0.000    0.504    0.618
##     ht                0.192    0.044    4.343    0.000    0.192    0.242
##     ha                0.091    0.062    1.474    0.141    0.091    0.100
##     pb                0.068    0.103    0.662    0.508    0.068    0.042
##     ps                0.898    0.100    9.013    0.000    0.898    0.567
##     pt                0.182    0.093    1.945    0.052    0.182    0.122
##     pa                0.350    0.112    3.132    0.002    0.350    0.188
##     fb                0.485    0.138    3.520    0.000    0.485    0.223
##     fs                1.370    0.151    9.097    0.000    1.370    0.601
##     ft                0.054    0.156    0.345    0.730    0.054    0.023
##     fa                0.512    0.149    3.439    0.001    0.512    0.204
summary(modfitW, standardized=T, rsq=T)
## lavaan 0.6-10 ended normally after 32 iterations
## 
##   Estimator                                         ML
##   Optimization method                           NLMINB
##   Number of model parameters                        29
##                                                       
##                                                   Used       Total
##   Number of observations                           210         312
##                                                                   
## Model Test User Model:
##                                                       
##   Test statistic                                 2.719
##   Degrees of freedom                                 4
##   P-value (Chi-square)                           0.606
## 
## Parameter Estimates:
## 
##   Standard errors                             Standard
##   Information                                 Expected
##   Information saturated (h1) model          Structured
## 
## Regressions:
##                     Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##   hzoop_gr ~                                                             
##     chla_1   (hb1)     0.031    0.035    0.885    0.376    0.031    0.057
##     hzoop_1  (hs1)    -0.260    0.037   -7.013    0.000   -0.260   -0.509
##     pzoop_1  (ht1)     0.016    0.034    0.480    0.631    0.016    0.032
##     potam_1  (ht2)    -0.090    0.035   -2.545    0.011   -0.090   -0.171
##     estfs__1 (ht3)     0.008    0.033    0.228    0.819    0.008    0.015
##     flow     (ha1)     0.073    0.037    2.000    0.046    0.073    0.140
##     temp     (ha2)    -0.007    0.032   -0.232    0.817   -0.007   -0.015
##     turbid   (ha3)    -0.098    0.036   -2.716    0.007   -0.098   -0.184
##   pzoop_gr ~                                                             
##     chla_1   (pb1)     0.178    0.054    3.333    0.001    0.178    0.211
##     hzoop_1  (pb2)     0.074    0.056    1.332    0.183    0.074    0.094
##     pzoop_1  (ps1)    -0.416    0.050   -8.233    0.000   -0.416   -0.525
##     potam_1  (pt1)    -0.075    0.054   -1.382    0.167   -0.075   -0.091
##     estfs__1 (pt2)     0.025    0.050    0.496    0.620    0.025    0.031
##     flow     (pa1)    -0.084    0.055   -1.528    0.127   -0.084   -0.103
##     temp     (pa2)     0.145    0.048    3.014    0.003    0.145    0.188
##     turbid   (pa3)     0.067    0.054    1.237    0.216    0.067    0.081
##   estfish_bsmt_gr ~                                                      
##     hzoop_1  (fb1)     0.151    0.105    1.443    0.149    0.151    0.092
##     pzoop_1  (fb2)    -0.123    0.101   -1.217    0.224   -0.123   -0.074
##     estfs__1 (fs1)    -1.006    0.106   -9.452    0.000   -1.006   -0.605
##     flow     (fa1)    -0.245    0.108   -2.260    0.024   -0.245   -0.145
##     temp     (fa2)     0.056    0.095    0.585    0.558    0.056    0.035
##     turbid   (fa3)     0.305    0.104    2.921    0.003    0.305    0.178
##     sbss1__1 (ft1)     0.267    0.103    2.600    0.009    0.267    0.160
## 
## Covariances:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##  .hzoop_gr ~~                                                           
##    .pzoop_gr          0.063    0.021    3.012    0.003    0.063    0.212
##    .estfsh_bsmt_gr   -0.119    0.042   -2.848    0.004   -0.119   -0.200
##  .pzoop_gr ~~                                                           
##    .estfsh_bsmt_gr   -0.034    0.061   -0.557    0.578   -0.034   -0.038
## 
## Variances:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##    .hzoop_gr          0.199    0.019   10.247    0.000    0.199    0.776
##    .pzoop_gr          0.444    0.043   10.247    0.000    0.444    0.722
##    .estfsh_bsmt_gr    1.773    0.173   10.247    0.000    1.773    0.666
## 
## R-Square:
##                    Estimate
##     hzoop_gr          0.224
##     pzoop_gr          0.278
##     estfsh_bsmt_gr    0.334
## 
## Defined Parameters:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##     hb                0.031    0.035    0.885    0.376    0.031    0.057
##     hs                0.260    0.037    7.013    0.000    0.260    0.509
##     ht                0.092    0.035    2.651    0.008    0.092    0.174
##     ha                0.122    0.040    3.056    0.002    0.122    0.231
##     pb                0.193    0.048    3.991    0.000    0.193    0.231
##     ps                0.416    0.050    8.233    0.000    0.416    0.525
##     pt                0.079    0.052    1.518    0.129    0.079    0.096
##     pa                0.180    0.054    3.323    0.001    0.180    0.229
##     fb                0.195    0.118    1.654    0.098    0.195    0.118
##     fs                1.006    0.106    9.452    0.000    1.006    0.605
##     ft                0.267    0.103    2.600    0.009    0.267    0.160
##     fa                0.395    0.120    3.290    0.001    0.395    0.232
summary(modfitN, standardized=T, rsq=T)
## lavaan 0.6-10 ended normally after 28 iterations
## 
##   Estimator                                         ML
##   Optimization method                           NLMINB
##   Number of model parameters                        31
##                                                       
##                                                   Used       Total
##   Number of observations                           193         312
##                                                                   
## Model Test User Model:
##                                                       
##   Test statistic                                 9.014
##   Degrees of freedom                                 8
##   P-value (Chi-square)                           0.341
## 
## Parameter Estimates:
## 
##   Standard errors                             Standard
##   Information                                 Expected
##   Information saturated (h1) model          Structured
## 
## Regressions:
##                     Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##   hzoop_gr ~                                                             
##     chla_1   (hb1)     0.040    0.053    0.748    0.455    0.040    0.043
##     hzoop_1  (hs1)    -0.536    0.052  -10.271    0.000   -0.536   -0.611
##     pzoop_1  (ht1)    -0.001    0.054   -0.027    0.979   -0.001   -0.002
##     corbic_1 (ht2)     0.027    0.050    0.535    0.593    0.027    0.030
##     estfs__1 (ht3)    -0.057    0.050   -1.133    0.257   -0.057   -0.071
##     flow     (ha1)     0.130    0.056    2.315    0.021    0.130    0.150
##     temp     (ha2)     0.036    0.049    0.727    0.467    0.036    0.043
##     turbid   (ha3)     0.150    0.052    2.911    0.004    0.150    0.170
##   pzoop_gr ~                                                             
##     chla_1   (pb1)     0.387    0.100    3.879    0.000    0.387    0.221
##     hzoop_1  (pb2)     0.194    0.097    2.007    0.045    0.194    0.118
##     pzoop_1  (ps1)    -1.032    0.100  -10.275    0.000   -1.032   -0.631
##     corbic_1 (pt1)     0.087    0.094    0.931    0.352    0.087    0.053
##     estfs__1 (pt2)    -0.093    0.093   -0.997    0.319   -0.093   -0.062
##     flow     (pa1)    -0.542    0.104   -5.224    0.000   -0.542   -0.336
##     temp     (pa2)     0.062    0.091    0.681    0.496    0.062    0.040
##     turbid   (pa3)     0.101    0.096    1.058    0.290    0.101    0.061
##   estfish_bsmt_gr ~                                                      
##     hzoop_1  (fb1)     0.330    0.178    1.856    0.063    0.330    0.124
##     pzoop_1  (fb2)     0.084    0.179    0.470    0.638    0.084    0.032
##     estfs__1 (fs1)    -1.435    0.171   -8.379    0.000   -1.435   -0.588
##     flow     (fa1)    -0.649    0.188   -3.452    0.001   -0.649   -0.248
##     temp     (fa2)     0.046    0.162    0.284    0.776    0.046    0.018
##     turbid   (fa3)     0.110    0.175    0.627    0.530    0.110    0.041
##     sside_1  (ft1)    -0.026    0.162   -0.161    0.872   -0.026   -0.010
##     cent_1   (ft2)    -0.264    0.165   -1.599    0.110   -0.264   -0.103
##     sbss1__1 (ft3)     0.187    0.170    1.103    0.270    0.187    0.073
## 
## Covariances:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##  .hzoop_gr ~~                                                           
##    .pzoop_gr          0.261    0.062    4.220    0.000    0.261    0.319
##    .estfsh_bsmt_gr   -0.203    0.106   -1.917    0.055   -0.203   -0.139
##  .pzoop_gr ~~                                                           
##    .estfsh_bsmt_gr    0.074    0.195    0.377    0.706    0.074    0.027
## 
## Variances:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##    .hzoop_gr          0.442    0.045    9.823    0.000    0.442    0.606
##    .pzoop_gr          1.521    0.155    9.823    0.000    1.521    0.595
##    .estfsh_bsmt_gr    4.818    0.490    9.823    0.000    4.818    0.717
## 
## R-Square:
##                    Estimate
##     hzoop_gr          0.394
##     pzoop_gr          0.405
##     estfsh_bsmt_gr    0.283
## 
## Defined Parameters:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##     hb                0.040    0.053    0.748    0.455    0.040    0.043
##     hs                0.536    0.052   10.271    0.000    0.536    0.611
##     ht                0.063    0.052    1.217    0.224    0.063    0.077
##     ha                0.201    0.050    4.006    0.000    0.201    0.231
##     pb                0.433    0.097    4.464    0.000    0.433    0.250
##     ps                1.032    0.100   10.275    0.000    1.032    0.631
##     pt                0.128    0.098    1.303    0.192    0.128    0.081
##     pa                0.555    0.104    5.343    0.000    0.555    0.344
##     fb                0.340    0.166    2.046    0.041    0.340    0.128
##     fs                1.435    0.171    8.379    0.000    1.435    0.588
##     ft                0.325    0.152    2.141    0.032    0.325    0.127
##     fa                0.660    0.190    3.477    0.001    0.660    0.252
summary(modfitS, standardized=T, rsq=T)
## lavaan 0.6-10 ended normally after 34 iterations
## 
##   Estimator                                         ML
##   Optimization method                           NLMINB
##   Number of model parameters                        32
##                                                       
##                                                   Used       Total
##   Number of observations                           199         312
##                                                                   
## Model Test User Model:
##                                                       
##   Test statistic                                 3.608
##   Degrees of freedom                                 7
##   P-value (Chi-square)                           0.824
## 
## Parameter Estimates:
## 
##   Standard errors                             Standard
##   Information                                 Expected
##   Information saturated (h1) model          Structured
## 
## Regressions:
##                     Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##   hzoop_gr ~                                                             
##     chla_1   (hb1)     0.139    0.047    2.974    0.003    0.139    0.182
##     hzoop_1  (hs1)    -0.410    0.045   -9.199    0.000   -0.410   -0.554
##     pzoop_1  (ht1)    -0.027    0.049   -0.557    0.578   -0.027   -0.035
##     corbic_1 (ht2)     0.035    0.045    0.774    0.439    0.035    0.046
##     estfs__1 (ht3)     0.005    0.045    0.111    0.911    0.005    0.007
##     flow     (ha1)     0.100    0.046    2.161    0.031    0.100    0.129
##     temp     (ha2)     0.050    0.043    1.156    0.248    0.050    0.069
##     turbid   (ha3)    -0.044    0.044   -1.012    0.312   -0.044   -0.061
##   pzoop_gr ~                                                             
##     chla_1   (pb1)     0.339    0.077    4.429    0.000    0.339    0.267
##     hzoop_1  (pb2)     0.121    0.073    1.654    0.098    0.121    0.098
##     pzoop_1  (ps1)    -0.769    0.080   -9.585    0.000   -0.769   -0.601
##     corbic_1 (pt1)    -0.017    0.073   -0.239    0.811   -0.017   -0.014
##     estfs__1 (pt2)     0.035    0.073    0.484    0.628    0.035    0.030
##     flow     (pa1)    -0.137    0.076   -1.809    0.070   -0.137   -0.106
##     temp     (pa2)    -0.043    0.071   -0.604    0.546   -0.043   -0.036
##     turbid   (pa3)     0.105    0.072    1.467    0.142    0.105    0.087
##   estfish_bsmt_gr ~                                                      
##     chla_1   (fb1)     0.232    0.183    1.272    0.204    0.232    0.078
##     hzoop_1  (fb2)     0.333    0.176    1.888    0.059    0.333    0.115
##     pzoop_1  (fb3)    -0.004    0.191   -0.020    0.984   -0.004   -0.001
##     estfs__1 (fs1)    -1.576    0.178   -8.874    0.000   -1.576   -0.561
##     flow     (fa1)    -0.145    0.183   -0.791    0.429   -0.145   -0.048
##     temp     (fa2)    -0.053    0.168   -0.316    0.752   -0.053   -0.019
##     turbid   (fa3)     0.462    0.185    2.491    0.013    0.462    0.162
##     sside_1  (ft1)    -0.027    0.166   -0.161    0.872   -0.027   -0.009
##     cent_1   (ft2)    -0.240    0.173   -1.390    0.165   -0.240   -0.087
##     sbss1__1 (ft3)     0.143    0.176    0.815    0.415    0.143    0.051
## 
## Covariances:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##  .hzoop_gr ~~                                                           
##    .pzoop_gr          0.176    0.043    4.108    0.000    0.176    0.304
##    .estfsh_bsmt_gr   -0.166    0.098   -1.693    0.090   -0.166   -0.121
##  .pzoop_gr ~~                                                           
##    .estfsh_bsmt_gr    0.384    0.162    2.374    0.018    0.384    0.171
## 
## Variances:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##    .hzoop_gr          0.353    0.035    9.975    0.000    0.353    0.680
##    .pzoop_gr          0.948    0.095    9.975    0.000    0.948    0.657
##    .estfsh_bsmt_gr    5.328    0.534    9.975    0.000    5.328    0.672
## 
## R-Square:
##                    Estimate
##     hzoop_gr          0.320
##     pzoop_gr          0.343
##     estfsh_bsmt_gr    0.328
## 
## Defined Parameters:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##     hb                0.139    0.047    2.974    0.003    0.139    0.182
##     hs                0.410    0.045    9.199    0.000    0.410    0.554
##     ht                0.044    0.048    0.922    0.357    0.044    0.058
##     ha                0.120    0.047    2.562    0.010    0.120    0.159
##     pb                0.360    0.074    4.889    0.000    0.360    0.285
##     ps                0.769    0.080    9.585    0.000    0.769    0.601
##     pt                0.039    0.072    0.549    0.583    0.039    0.033
##     pa                0.178    0.078    2.293    0.022    0.178    0.142
##     fb                0.406    0.169    2.407    0.016    0.406    0.139
##     fs                1.576    0.178    8.874    0.000    1.576    0.561
##     ft                0.281    0.183    1.531    0.126    0.281    0.101
##     fa                0.487    0.195    2.501    0.012    0.487    0.170
#modificationindices(modfitW, sort=T, maximum.number=20)
#residuals(modfitS)

labelsfarwest=createLabels(modfitFW, cnameslag)
labelswest=createLabels(modfitW, cnameslag)
labelsnorth=createLabels(modfitN, cnameslag)
labelssouth=createLabels(modfitS, cnameslag)


#FAR WEST
upper_plot_far_west <- createGraph(fit=modfitFW, 
                                   reference_df=cnameslag, 
                                   model_type="monthly_upper_trophic",
                                   title="Far West",
                                   manual_port_settings=TRUE)
upper_plot_far_west
#WEST
upper_plot_west <- createGraph(fit=modfitW, 
                               reference_df=cnameslag, 
                               model_type="monthly_upper_trophic",
                               title="West",
                               manual_port_settings=TRUE)
upper_plot_west
#NORTH
upper_plot_north <- createGraph(fit=modfitN, 
                                reference_df=cnameslag, 
                                model_type="monthly_upper_trophic",
                                title="North",
                                manual_port_settings=TRUE)
upper_plot_north
#SOUTH
upper_plot_south <- createGraph(fit=modfitS, 
                                reference_df=cnameslag, 
                                model_type="monthly_upper_trophic",
                                title="South",
                                manual_port_settings=TRUE)
upper_plot_south

Lower trophic

modFW='din_gr~ns1*din_1+nt1*chla_gr+nn1*hzoop_1+nn2*pzoop_1+nn3*potam_1+na1*flow+na2*temp+na3*turbid
        chla_gr~cb1*din_1+cs1*chla_1+ct1*hzoop_1+ct2*potam_1+ca1*flow+ca2*temp+ca3*turbid
        potam~lb1*chla_1+lb2*hzoop_1+lb3*pzoop_1+ls1*potam_1+la1*flow+la2*temp+la3*turbid
        
        ns:=sqrt(ns1^2)
        nt:=sqrt(nt1^2)
        nn:=sqrt(nn1^2+nn2^2+nn3^2)
        na:=sqrt(na1^2+na2^2+na3^2)
        
        cb:=sqrt(cb1^2)
        cs:=sqrt(cs1^2)
        ct:=sqrt(ct1^2+ct2^2)
        ca:=sqrt(ca1^2+ca2^2+ca3^2)
        
        lb:=sqrt(lb1^2+lb2^2+lb3^2)
        ls:=sqrt(ls1^2)
        la:=sqrt(la1^2+la2^2+la3^2)
'

modW='din_gr~ns1*din_1+nt1*chla_gr+nn1*hzoop_1+nn2*pzoop_1+nn3*potam_1+na1*flow+na2*temp+na3*turbid
        chla_gr~cb1*din_1+cs1*chla_1+ct1*hzoop_1+ct2*potam_1+ca1*flow+ca2*temp+ca3*turbid
        potam~lb1*din_1+lb2*chla_1+lb3*hzoop_1+lb4*pzoop_1+ls1*potam_1+la1*flow+la2*temp+la3*turbid
        
        ns:=sqrt(ns1^2)
        nt:=sqrt(nt1^2)
        nn:=sqrt(nn1^2+nn2^2+nn3^2)
        na:=sqrt(na1^2+na2^2+na3^2)
        
        cb:=sqrt(cb1^2)
        cs:=sqrt(cs1^2)
        ct:=sqrt(ct1^2+ct2^2)
        ca:=sqrt(ca1^2+ca2^2+ca3^2)
        
        lb:=sqrt(lb1^2+lb2^2+lb3^2+lb4^2)
        ls:=sqrt(ls1^2)
        la:=sqrt(la1^2+la2^2+la3^2)
'

modN='din_gr~ns1*din_1+nt1*chla_gr+nn1*hzoop_1+nn2*pzoop_1+nn3*corbic_1+na1*flow+na2*temp+na3*turbid
        chla_gr~cb1*din_1+cs1*chla_1+ct1*hzoop_1+ct2*corbic_1+ct3*pzoop_1+ca1*flow+ca2*temp+ca3*turbid
        corbic~lb1*chla_1+lb2*hzoop_1+lb3*pzoop_1+ls1*corbic_1+la1*flow+la2*temp+la3*turbid
        
        ns:=sqrt(ns1^2)
        nt:=sqrt(nt1^2)
        nn:=sqrt(nn1^2+nn2^2+nn3^2)
        na:=sqrt(na1^2+na2^2+na3^2)
        
        cb:=sqrt(cb1^2)
        cs:=sqrt(cs1^2)
        ct:=sqrt(ct1^2+ct2^2+ct3^2)
        ca:=sqrt(ca1^2+ca2^2+ca3^2)
        
        lb:=sqrt(lb1^2+lb2^2+lb3^2)
        ls:=sqrt(ls1^2)
        la:=sqrt(la1^2+la2^2+la3^2)
'

modS='din_gr~ns1*din_1+nt1*chla_gr+nn1*hzoop_1+nn2*pzoop_1+nn3*corbic_1+na1*flow+na2*temp+na3*turbid
        chla_gr~cb1*din_1+cs1*chla_1+ct1*hzoop_1+ct2*corbic_1+ca1*flow+ca2*temp+ca3*turbid
        corbic~lb1*chla_1+lb2*hzoop_1+lb3*pzoop_1+ls1*corbic_1+la1*flow+la2*temp+la3*turbid
        
        ns:=sqrt(ns1^2)
        nt:=sqrt(nt1^2)
        nn:=sqrt(nn1^2+nn2^2+nn3^2)
        na:=sqrt(na1^2+na2^2+na3^2)
        
        cb:=sqrt(cb1^2)
        cs:=sqrt(cs1^2)
        ct:=sqrt(ct1^2+ct2^2)
        ca:=sqrt(ca1^2+ca2^2+ca3^2)
        
        lb:=sqrt(lb1^2+lb2^2+lb3^2)
        ls:=sqrt(ls1^2)
        la:=sqrt(la1^2+la2^2+la3^2)
'

modfitFW=sem(modFW, data=filter(fdr_ds,region=="Far West"))
modfitW=sem(modW, data=filter(fdr_ds,region=="West"))
modfitN=sem(modN, data=filter(fdr_ds,region=="North"))
modfitS=sem(modS, data=filter(fdr_ds,region=="South"))
summary(modfitFW, standardized=T, rsq=T)
## lavaan 0.6-10 ended normally after 20 iterations
## 
##   Estimator                                         ML
##   Optimization method                           NLMINB
##   Number of model parameters                        26
##                                                       
##                                                   Used       Total
##   Number of observations                           234         312
##                                                                   
## Model Test User Model:
##                                                       
##   Test statistic                                 5.259
##   Degrees of freedom                                 4
##   P-value (Chi-square)                           0.262
## 
## Parameter Estimates:
## 
##   Standard errors                             Standard
##   Information                                 Expected
##   Information saturated (h1) model          Structured
## 
## Regressions:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##   din_gr ~                                                              
##     din_1    (ns1)   -0.218    0.025   -8.695    0.000   -0.218   -0.487
##     chla_gr  (nt1)   -0.160    0.051   -3.132    0.002   -0.160   -0.175
##     hzoop_1  (nn1)    0.000    0.026    0.009    0.993    0.000    0.001
##     pzoop_1  (nn2)   -0.010    0.025   -0.404    0.686   -0.010   -0.023
##     potam_1  (nn3)   -0.001    0.025   -0.059    0.953   -0.001   -0.003
##     flow     (na1)    0.003    0.029    0.114    0.909    0.003    0.007
##     temp     (na2)   -0.046    0.028   -1.652    0.099   -0.046   -0.099
##     turbid   (na3)   -0.054    0.029   -1.840    0.066   -0.054   -0.114
##   chla_gr ~                                                             
##     din_1    (cb1)    0.000    0.027    0.001    0.999    0.000    0.000
##     chla_1   (cs1)   -0.323    0.034   -9.624    0.000   -0.323   -0.538
##     hzoop_1  (ct1)   -0.001    0.028   -0.047    0.963   -0.001   -0.003
##     potam_1  (ct2)   -0.014    0.027   -0.540    0.589   -0.014   -0.030
##     flow     (ca1)    0.014    0.031    0.462    0.644    0.014    0.028
##     temp     (ca2)    0.044    0.030    1.466    0.143    0.044    0.086
##     turbid   (ca3)   -0.025    0.032   -0.789    0.430   -0.025   -0.048
##   potam ~                                                               
##     chla_1   (lb1)    0.058    0.060    0.962    0.336    0.058    0.046
##     hzoop_1  (lb2)   -0.079    0.051   -1.543    0.123   -0.079   -0.076
##     pzoop_1  (lb3)   -0.162    0.050   -3.251    0.001   -0.162   -0.160
##     potam_1  (ls1)    0.628    0.048   13.006    0.000    0.628    0.629
##     flow     (la1)    0.112    0.057    1.962    0.050    0.112    0.102
##     temp     (la2)   -0.043    0.054   -0.801    0.423   -0.043   -0.040
##     turbid   (la3)    0.038    0.058    0.647    0.517    0.038    0.034
## 
## Covariances:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##  .din_gr ~~                                                             
##    .potam            -0.017    0.019   -0.910    0.363   -0.017   -0.060
## 
## Variances:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##    .din_gr            0.147    0.014   10.817    0.000    0.147    0.708
##    .chla_gr           0.172    0.016   10.817    0.000    0.172    0.694
##    .potam             0.567    0.052   10.817    0.000    0.567    0.517
## 
## R-Square:
##                    Estimate
##     din_gr            0.292
##     chla_gr           0.306
##     potam             0.483
## 
## Defined Parameters:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##     ns                0.218    0.025    8.695    0.000    0.218    0.487
##     nt                0.160    0.051    3.132    0.002    0.160    0.175
##     nn                0.010    0.026    0.406    0.685    0.010    0.024
##     na                0.071    0.032    2.212    0.027    0.071    0.151
##     cb                0.000    0.027    0.001    0.999    0.000    0.000
##     cs                0.323    0.034    9.624    0.000    0.323    0.538
##     ct                0.014    0.027    0.532    0.595    0.014    0.030
##     ca                0.053    0.029    1.789    0.074    0.053    0.102
##     lb                0.189    0.049    3.863    0.000    0.189    0.183
##     ls                0.628    0.048   13.006    0.000    0.628    0.629
##     la                0.126    0.049    2.582    0.010    0.126    0.115
summary(modfitW, standardized=T, rsq=T)
## lavaan 0.6-10 ended normally after 25 iterations
## 
##   Estimator                                         ML
##   Optimization method                           NLMINB
##   Number of model parameters                        27
##                                                       
##                                                   Used       Total
##   Number of observations                           257         312
##                                                                   
## Model Test User Model:
##                                                       
##   Test statistic                                17.574
##   Degrees of freedom                                 3
##   P-value (Chi-square)                           0.001
## 
## Parameter Estimates:
## 
##   Standard errors                             Standard
##   Information                                 Expected
##   Information saturated (h1) model          Structured
## 
## Regressions:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##   din_gr ~                                                              
##     din_1    (ns1)   -0.196    0.020   -9.636    0.000   -0.196   -0.566
##     chla_gr  (nt1)   -0.122    0.033   -3.698    0.000   -0.122   -0.191
##     hzoop_1  (nn1)   -0.009    0.020   -0.464    0.643   -0.009   -0.028
##     pzoop_1  (nn2)    0.008    0.019    0.432    0.665    0.008    0.024
##     potam_1  (nn3)    0.021    0.021    1.020    0.308    0.021    0.062
##     flow     (na1)   -0.122    0.021   -5.722    0.000   -0.122   -0.344
##     temp     (na2)    0.020    0.018    1.087    0.277    0.020    0.058
##     turbid   (na3)    0.040    0.020    2.010    0.044    0.040    0.115
##   chla_gr ~                                                             
##     din_1    (cb1)   -0.064    0.032   -1.967    0.049   -0.064   -0.118
##     chla_1   (cs1)   -0.370    0.034  -11.038    0.000   -0.370   -0.618
##     hzoop_1  (ct1)    0.049    0.030    1.612    0.107    0.049    0.093
##     potam_1  (ct2)    0.013    0.032    0.396    0.692    0.013    0.024
##     flow     (ca1)    0.001    0.033    0.044    0.965    0.001    0.003
##     temp     (ca2)   -0.042    0.028   -1.458    0.145   -0.042   -0.078
##     turbid   (ca3)   -0.014    0.031   -0.450    0.653   -0.014   -0.026
##   potam ~                                                               
##     din_1    (lb1)    0.075    0.044    1.712    0.087    0.075    0.074
##     chla_1   (lb2)    0.001    0.045    0.015    0.988    0.001    0.001
##     hzoop_1  (lb3)   -0.032    0.043   -0.752    0.452   -0.032   -0.033
##     pzoop_1  (lb4)    0.077    0.040    1.927    0.054    0.077    0.077
##     potam_1  (ls1)    0.702    0.044   15.987    0.000    0.702    0.697
##     flow     (la1)   -0.108    0.045   -2.405    0.016   -0.108   -0.104
##     temp     (la2)   -0.010    0.039   -0.262    0.793   -0.010   -0.010
##     turbid   (la3)   -0.079    0.042   -1.890    0.059   -0.079   -0.078
## 
## Covariances:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##  .din_gr ~~                                                             
##    .potam             0.013    0.011    1.221    0.222    0.013    0.076
## 
## Variances:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##    .din_gr            0.081    0.007   11.336    0.000    0.081    0.681
##    .chla_gr           0.195    0.017   11.336    0.000    0.195    0.673
##    .potam             0.358    0.032   11.336    0.000    0.358    0.351
## 
## R-Square:
##                    Estimate
##     din_gr            0.319
##     chla_gr           0.327
##     potam             0.649
## 
## Defined Parameters:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##     ns                0.196    0.020    9.636    0.000    0.196    0.566
##     nt                0.122    0.033    3.698    0.000    0.122    0.191
##     nn                0.025    0.021    1.194    0.232    0.025    0.072
##     na                0.130    0.022    5.860    0.000    0.130    0.367
##     cb                0.064    0.032    1.967    0.049    0.064    0.118
##     cs                0.370    0.034   11.038    0.000    0.370    0.618
##     ct                0.050    0.032    1.573    0.116    0.050    0.096
##     ca                0.044    0.030    1.444    0.149    0.044    0.082
##     lb                0.113    0.044    2.583    0.010    0.113    0.112
##     ls                0.702    0.044   15.987    0.000    0.702    0.697
##     la                0.134    0.040    3.330    0.001    0.134    0.130
summary(modfitN, standardized=T, rsq=T)
## lavaan 0.6-10 ended normally after 19 iterations
## 
##   Estimator                                         ML
##   Optimization method                           NLMINB
##   Number of model parameters                        27
##                                                       
##                                                   Used       Total
##   Number of observations                           255         312
##                                                                   
## Model Test User Model:
##                                                       
##   Test statistic                                23.281
##   Degrees of freedom                                 3
##   P-value (Chi-square)                           0.000
## 
## Parameter Estimates:
## 
##   Standard errors                             Standard
##   Information                                 Expected
##   Information saturated (h1) model          Structured
## 
## Regressions:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##   din_gr ~                                                              
##     din_1    (ns1)   -0.336    0.026  -13.176    0.000   -0.336   -0.679
##     chla_gr  (nt1)   -0.108    0.033   -3.258    0.001   -0.108   -0.155
##     hzoop_1  (nn1)    0.012    0.025    0.503    0.615    0.012    0.025
##     pzoop_1  (nn2)    0.057    0.026    2.203    0.028    0.057    0.113
##     corbic_1 (nn3)   -0.010    0.024   -0.407    0.684   -0.010   -0.019
##     flow     (na1)   -0.176    0.027   -6.474    0.000   -0.176   -0.344
##     temp     (na2)    0.020    0.024    0.842    0.400    0.020    0.041
##     turbid   (na3)    0.016    0.023    0.692    0.489    0.016    0.033
##   chla_gr ~                                                             
##     din_1    (cb1)    0.012    0.040    0.306    0.760    0.012    0.017
##     chla_1   (cs1)   -0.398    0.037  -10.808    0.000   -0.398   -0.561
##     hzoop_1  (ct1)   -0.016    0.038   -0.411    0.681   -0.016   -0.022
##     corbic_1 (ct2)    0.013    0.038    0.350    0.727    0.013    0.018
##     pzoop_1  (ct3)   -0.087    0.040   -2.153    0.031   -0.087   -0.119
##     flow     (ca1)   -0.048    0.042   -1.137    0.256   -0.048   -0.066
##     temp     (ca2)    0.058    0.038    1.555    0.120    0.058    0.082
##     turbid   (ca3)    0.046    0.036    1.276    0.202    0.046    0.066
##   corbic ~                                                              
##     chla_1   (lb1)   -0.001    0.053   -0.021    0.983   -0.001   -0.001
##     hzoop_1  (lb2)    0.015    0.056    0.264    0.792    0.015    0.015
##     pzoop_1  (lb3)   -0.011    0.058   -0.191    0.849   -0.011   -0.011
##     corbic_1 (ls1)    0.463    0.056    8.308    0.000    0.463    0.460
##     flow     (la1)    0.092    0.060    1.538    0.124    0.092    0.091
##     temp     (la2)   -0.034    0.055   -0.615    0.539   -0.034   -0.035
##     turbid   (la3)   -0.117    0.053   -2.208    0.027   -0.117   -0.121
## 
## Covariances:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##  .din_gr ~~                                                             
##    .corbic           -0.010    0.019   -0.506    0.613   -0.010   -0.032
## 
## Variances:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##    .din_gr            0.135    0.012   11.292    0.000    0.135    0.547
##    .chla_gr           0.331    0.029   11.292    0.000    0.331    0.647
##    .corbic            0.715    0.063   11.292    0.000    0.715    0.740
## 
## R-Square:
##                    Estimate
##     din_gr            0.453
##     chla_gr           0.353
##     corbic            0.260
## 
## Defined Parameters:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##     ns                0.336    0.026   13.176    0.000    0.336    0.679
##     nt                0.108    0.033    3.258    0.001    0.108    0.155
##     nn                0.059    0.024    2.423    0.015    0.059    0.117
##     na                0.177    0.027    6.594    0.000    0.177    0.348
##     cb                0.012    0.040    0.306    0.760    0.012    0.017
##     cs                0.398    0.037   10.808    0.000    0.398    0.561
##     ct                0.089    0.038    2.330    0.020    0.089    0.122
##     ca                0.089    0.038    2.328    0.020    0.089    0.124
##     lb                0.019    0.062    0.299    0.765    0.019    0.019
##     ls                0.463    0.056    8.308    0.000    0.463    0.460
##     la                0.152    0.057    2.684    0.007    0.152    0.155
summary(modfitS, standardized=T, rsq=T)
## lavaan 0.6-10 ended normally after 19 iterations
## 
##   Estimator                                         ML
##   Optimization method                           NLMINB
##   Number of model parameters                        26
##                                                       
##                                                   Used       Total
##   Number of observations                           256         312
##                                                                   
## Model Test User Model:
##                                                       
##   Test statistic                                 2.520
##   Degrees of freedom                                 4
##   P-value (Chi-square)                           0.641
## 
## Parameter Estimates:
## 
##   Standard errors                             Standard
##   Information                                 Expected
##   Information saturated (h1) model          Structured
## 
## Regressions:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##   din_gr ~                                                              
##     din_1    (ns1)   -0.297    0.028  -10.573    0.000   -0.297   -0.577
##     chla_gr  (nt1)   -0.100    0.035   -2.890    0.004   -0.100   -0.148
##     hzoop_1  (nn1)   -0.013    0.029   -0.433    0.665   -0.013   -0.023
##     pzoop_1  (nn2)   -0.011    0.030   -0.361    0.718   -0.011   -0.019
##     corbic_1 (nn3)    0.038    0.027    1.372    0.170    0.038    0.073
##     flow     (na1)   -0.008    0.028   -0.278    0.781   -0.008   -0.014
##     temp     (na2)    0.045    0.027    1.657    0.097    0.045    0.086
##     turbid   (na3)    0.092    0.029    3.185    0.001    0.092    0.176
##   chla_gr ~                                                             
##     din_1    (cb1)   -0.017    0.042   -0.402    0.688   -0.017   -0.022
##     chla_1   (cs1)   -0.441    0.042  -10.587    0.000   -0.441   -0.566
##     hzoop_1  (ct1)    0.060    0.044    1.354    0.176    0.060    0.074
##     corbic_1 (ct2)    0.048    0.041    1.169    0.242    0.048    0.063
##     flow     (ca1)   -0.076    0.042   -1.809    0.070   -0.076   -0.096
##     temp     (ca2)    0.008    0.041    0.189    0.850    0.008    0.010
##     turbid   (ca3)    0.014    0.044    0.317    0.751    0.014    0.018
##   corbic ~                                                              
##     chla_1   (lb1)    0.047    0.059    0.789    0.430    0.047    0.046
##     hzoop_1  (lb2)   -0.029    0.061   -0.474    0.635   -0.029   -0.028
##     pzoop_1  (lb3)   -0.039    0.063   -0.627    0.531   -0.039   -0.037
##     corbic_1 (ls1)    0.316    0.058    5.483    0.000    0.316    0.319
##     flow     (la1)    0.082    0.058    1.397    0.162    0.082    0.080
##     temp     (la2)   -0.078    0.058   -1.347    0.178   -0.078   -0.077
##     turbid   (la3)    0.185    0.058    3.209    0.001    0.185    0.186
## 
## Covariances:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##  .din_gr ~~                                                             
##    .corbic           -0.024    0.024   -0.981    0.327   -0.024   -0.061
## 
## Variances:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##    .din_gr            0.182    0.016   11.314    0.000    0.182    0.663
##    .chla_gr           0.415    0.037   11.314    0.000    0.415    0.688
##    .corbic            0.812    0.072   11.314    0.000    0.812    0.809
## 
## R-Square:
##                    Estimate
##     din_gr            0.337
##     chla_gr           0.312
##     corbic            0.191
## 
## Defined Parameters:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##     ns                0.297    0.028   10.573    0.000    0.297    0.577
##     nt                0.100    0.035    2.890    0.004    0.100    0.148
##     nn                0.041    0.028    1.466    0.143    0.041    0.079
##     na                0.102    0.029    3.501    0.000    0.102    0.196
##     cb                0.017    0.042    0.402    0.688    0.017    0.022
##     cs                0.441    0.042   10.587    0.000    0.441    0.566
##     ct                0.077    0.041    1.868    0.062    0.077    0.097
##     ca                0.077    0.042    1.818    0.069    0.077    0.098
##     lb                0.068    0.066    1.029    0.303    0.068    0.066
##     ls                0.316    0.058    5.483    0.000    0.316    0.319
##     la                0.217    0.055    3.923    0.000    0.217    0.217
#modificationindices(modfitW, sort=T, maximum.number=20)
#residuals(modfitW)

labelsfarwest=createLabels(modfitFW, cnameslag)
labelswest=createLabels(modfitW, cnameslag)
labelsnorth=createLabels(modfitN, cnameslag)
labelssouth=createLabels(modfitS, cnameslag)

#FAR WEST
lower_plot_far_west <- createGraph(fit=modfitFW, 
                                   reference_df=cnameslag, 
                                   model_type="monthly_lower_trophic",
                                   title="Far West",
                                   manual_port_settings=TRUE)
lower_plot_far_west
#WEST
lower_plot_west <- createGraph(fit=modfitW, 
                               reference_df=cnameslag, 
                               model_type="monthly_lower_trophic",
                               title="West",
                               manual_port_settings=TRUE)
lower_plot_west
#NORTH
lower_plot_north <- createGraph(fit=modfitN, 
                                reference_df=cnameslag, 
                                model_type="monthly_lower_trophic",
                                title="North",
                                manual_port_settings=TRUE)
lower_plot_north
#SOUTH
lower_plot_south <- createGraph(fit=modfitS, 
                                reference_df=cnameslag, 
                                model_type="monthly_lower_trophic",
                                title="South",
                                manual_port_settings=TRUE)
lower_plot_south

Zooplankton

modFW='chla_gr~chla_1+hcope_1+amphi_m_1+rotif_m_1+potam_1+flow+turbid+temp
       hcope_gr~chla_1+hcope_1+pcope_1+potam_1+flow+turbid+temp+estfish_bsmt_1
       amphi_m_gr~chla_1+amphi_m_1+flow+turbid+temp+estfish_bsmt_1
       rotif_m_gr~chla_1+rotif_m_1+flow+turbid+temp+estfish_bsmt_1
       pcope_gr~hcope_1+pcope_1+potam_1+flow+turbid+temp+estfish_bsmt_1
       estfish_bsmt_gr~estfish_bsmt_1+hcope_1+pcope_1+amphi_m_1+rotif_m_1+flow+turbid+temp
'
modW='chla_gr~chla_1+hcope_1+amphi_m_1+rotif_m_1+potam_1+flow+turbid+temp+mysid_1
       hcope_gr~chla_1+hcope_1+pcope_1+mysid_1+potam_1+flow+turbid+temp+estfish_bsmt_1+rotif_m_1
       amphi_m_gr~chla_1+amphi_m_1+mysid_1+flow+turbid+temp+estfish_bsmt_1
       rotif_m_gr~chla_1+rotif_m_1+flow+turbid+temp+estfish_bsmt_1
       pcope_gr~hcope_1+pcope_1+mysid_1+potam_1+flow+turbid+temp+estfish_bsmt_1+rotif_m_1
       mysid_gr~chla_1+hcope_1+pcope_1+amphi_m_1+mysid_1+flow+turbid+temp+estfish_bsmt_1
       estfish_bsmt_gr~estfish_bsmt_1+hcope_1+pcope_1+amphi_m_1+rotif_m_1+mysid_1+flow+turbid+temp
'
modN='chla_gr~chla_1+hcope_1+amphi_m_1+rotif_m_1+corbic_1+flow+turbid+temp
       hcope_gr~chla_1+hcope_1+pcope_1+mysid_1+corbic_1+flow+turbid+temp+estfish_bsmt_1
       amphi_m_gr~chla_1+amphi_m_1+flow+turbid+temp+estfish_bsmt_1
       rotif_m_gr~chla_1+rotif_m_1+flow+turbid+temp+estfish_bsmt_1
       pcope_gr~hcope_1+pcope_1+mysid_1+corbic_1+flow+turbid+temp+estfish_bsmt_1+chla_1
       mysid_gr~hcope_1+pcope_1+mysid_1+amphi_m_1+flow+turbid+temp+estfish_bsmt_1
       estfish_bsmt_gr~estfish_bsmt_1+hcope_1+pcope_1+amphi_m_1+rotif_m_1+mysid_1+flow+turbid+temp
'
modS='chla_gr~chla_1+hcope_1+clad_1+rotif_m_1+corbic_1+flow+turbid+temp
       hcope_gr~chla_1+hcope_1+pcope_1+corbic_1+flow+turbid+temp+estfish_bsmt_1
       clad_gr~chla_1+clad_1+pcope_1+flow+turbid+temp+estfish_bsmt_1
       amphi_m_gr~chla_1+amphi_m_1+flow+turbid+temp+estfish_bsmt_1
       rotif_m_gr~chla_1+rotif_m_1+flow+turbid+temp+estfish_bsmt_1
       pcope_gr~chla_1+hcope_1+clad_1+pcope_1+corbic_1+flow+turbid+temp+estfish_bsmt_1
       estfish_bsmt_gr~estfish_bsmt_1+hcope_1+pcope_1+amphi_m_1+rotif_m_1+clad_1+flow+turbid+temp
'
modfitFW=sem(modFW, data=filter(fdr_ds,region=="Far West"))
modfitW=sem(modW, data=filter(fdr_ds,region=="West"))
modfitN=sem(modN, data=filter(fdr_ds,region=="North"))
modfitS=sem(modS, data=filter(fdr_ds,region=="South"))
summary(modfitFW, standardized=T, rsq=T)
## lavaan 0.6-10 ended normally after 48 iterations
## 
##   Estimator                                         ML
##   Optimization method                           NLMINB
##   Number of model parameters                        64
##                                                       
##                                                   Used       Total
##   Number of observations                           183         312
##                                                                   
## Model Test User Model:
##                                                       
##   Test statistic                                26.025
##   Degrees of freedom                                17
##   P-value (Chi-square)                           0.074
## 
## Parameter Estimates:
## 
##   Standard errors                             Standard
##   Information                                 Expected
##   Information saturated (h1) model          Structured
## 
## Regressions:
##                     Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##   chla_gr ~                                                              
##     chla_1            -0.338    0.037   -9.194    0.000   -0.338   -0.564
##     hcope_1            0.047    0.030    1.558    0.119    0.047    0.096
##     amphi_m_1          0.006    0.036    0.177    0.860    0.006    0.013
##     rotif_m_1         -0.046    0.034   -1.347    0.178   -0.046   -0.087
##     potam_1           -0.010    0.027   -0.357    0.721   -0.010   -0.022
##     flow               0.031    0.039    0.788    0.430    0.031    0.060
##     turbid            -0.039    0.039   -0.993    0.321   -0.039   -0.070
##     temp               0.028    0.034    0.826    0.409    0.028    0.053
##   hcope_gr ~                                                             
##     chla_1             0.147    0.080    1.840    0.066    0.147    0.103
##     hcope_1           -0.723    0.070  -10.400    0.000   -0.723   -0.628
##     pcope_1            0.065    0.072    0.902    0.367    0.065    0.054
##     potam_1           -0.114    0.061   -1.848    0.065   -0.114   -0.108
##     flow              -0.074    0.081   -0.913    0.361   -0.074   -0.060
##     turbid            -0.047    0.085   -0.556    0.578   -0.047   -0.036
##     temp              -0.047    0.077   -0.612    0.540   -0.047   -0.037
##     estfish_bsmt_1    -0.137    0.077   -1.786    0.074   -0.137   -0.114
##   amphi_m_gr ~                                                           
##     chla_1             0.071    0.083    0.859    0.390    0.071    0.056
##     amphi_m_1         -0.532    0.079   -6.688    0.000   -0.532   -0.520
##     flow              -0.510    0.089   -5.740    0.000   -0.510   -0.467
##     turbid             0.004    0.086    0.043    0.966    0.004    0.003
##     temp               0.063    0.077    0.823    0.411    0.063    0.057
##     estfish_bsmt_1     0.096    0.074    1.296    0.195    0.096    0.090
##   rotif_m_gr ~                                                           
##     chla_1            -0.414    0.174   -2.379    0.017   -0.414   -0.145
##     rotif_m_1         -1.389    0.154   -9.043    0.000   -1.389   -0.549
##     flow               0.086    0.172    0.499    0.618    0.086    0.035
##     turbid             0.138    0.182    0.758    0.449    0.138    0.052
##     temp              -0.027    0.163   -0.169    0.866   -0.027   -0.011
##     estfish_bsmt_1    -0.046    0.154   -0.299    0.765   -0.046   -0.019
##   pcope_gr ~                                                             
##     hcope_1            0.137    0.134    1.023    0.306    0.137    0.064
##     pcope_1           -1.288    0.138   -9.324    0.000   -1.288   -0.579
##     potam_1           -0.198    0.117   -1.688    0.091   -0.198   -0.102
##     flow               0.357    0.156    2.294    0.022    0.357    0.157
##     turbid             0.206    0.164    1.254    0.210    0.206    0.084
##     temp               0.240    0.148    1.621    0.105    0.240    0.103
##     estfish_bsmt_1    -0.027    0.147   -0.185    0.853   -0.027   -0.012
##   estfish_bsmt_gr ~                                                      
##     estfish_bsmt_1    -1.325    0.150   -8.810    0.000   -1.325   -0.589
##     hcope_1           -0.208    0.136   -1.530    0.126   -0.208   -0.097
##     pcope_1            0.331    0.141    2.352    0.019    0.331    0.147
##     amphi_m_1         -0.142    0.160   -0.890    0.374   -0.142   -0.066
##     rotif_m_1         -0.320    0.147   -2.182    0.029   -0.320   -0.136
##     flow               0.141    0.172    0.821    0.412    0.141    0.061
##     turbid             0.450    0.169    2.665    0.008    0.450    0.182
##     temp              -0.089    0.151   -0.591    0.555   -0.089   -0.038
## 
## Covariances:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##  .chla_gr ~~                                                            
##    .hcope_gr          0.022    0.029    0.755    0.450    0.022    0.056
##    .amphi_m_gr       -0.003    0.029   -0.120    0.904   -0.003   -0.009
##    .rotif_m_gr        0.161    0.063    2.574    0.010    0.161    0.194
##    .pcope_gr          0.044    0.056    0.792    0.428    0.044    0.059
##    .estfsh_bsmt_gr   -0.058    0.056   -1.022    0.307   -0.058   -0.076
##  .hcope_gr ~~                                                           
##    .amphi_m_gr       -0.033    0.065   -0.513    0.608   -0.033   -0.038
##    .rotif_m_gr        0.167    0.138    1.205    0.228    0.167    0.089
##    .pcope_gr         -0.371    0.127   -2.915    0.004   -0.371   -0.221
##    .estfsh_bsmt_gr   -0.095    0.126   -0.753    0.452   -0.095   -0.056
##  .amphi_m_gr ~~                                                         
##    .rotif_m_gr       -0.259    0.139   -1.863    0.062   -0.259   -0.139
##    .pcope_gr          0.019    0.125    0.152    0.879    0.019    0.011
##    .estfsh_bsmt_gr   -0.004    0.126   -0.034    0.973   -0.004   -0.002
##  .rotif_m_gr ~~                                                         
##    .pcope_gr         -0.230    0.266   -0.865    0.387   -0.230   -0.064
##    .estfsh_bsmt_gr   -0.275    0.269   -1.023    0.306   -0.275   -0.076
##  .pcope_gr ~~                                                           
##    .estfsh_bsmt_gr   -0.522    0.245   -2.129    0.033   -0.522   -0.159
## 
## Variances:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##    .chla_gr           0.174    0.018    9.566    0.000    0.174    0.674
##    .hcope_gr          0.873    0.091    9.566    0.000    0.873    0.595
##    .amphi_m_gr        0.875    0.091    9.566    0.000    0.875    0.755
##    .rotif_m_gr        3.973    0.415    9.566    0.000    3.973    0.670
##    .pcope_gr          3.243    0.339    9.566    0.000    3.243    0.645
##    .estfsh_bsmt_gr    3.311    0.346    9.566    0.000    3.311    0.643
## 
## R-Square:
##                    Estimate
##     chla_gr           0.326
##     hcope_gr          0.405
##     amphi_m_gr        0.245
##     rotif_m_gr        0.330
##     pcope_gr          0.355
##     estfsh_bsmt_gr    0.357
summary(modfitW, standardized=T, rsq=T)
## lavaan 0.6-10 ended normally after 45 iterations
## 
##   Estimator                                         ML
##   Optimization method                           NLMINB
##   Number of model parameters                        87
##                                                       
##                                                   Used       Total
##   Number of observations                           202         312
##                                                                   
## Model Test User Model:
##                                                       
##   Test statistic                                18.548
##   Degrees of freedom                                18
##   P-value (Chi-square)                           0.420
## 
## Parameter Estimates:
## 
##   Standard errors                             Standard
##   Information                                 Expected
##   Information saturated (h1) model          Structured
## 
## Regressions:
##                     Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##   chla_gr ~                                                              
##     chla_1            -0.348    0.037   -9.389    0.000   -0.348   -0.595
##     hcope_1            0.046    0.036    1.265    0.206    0.046    0.081
##     amphi_m_1          0.047    0.035    1.320    0.187    0.047    0.087
##     rotif_m_1          0.063    0.033    1.891    0.059    0.063    0.123
##     potam_1           -0.021    0.037   -0.568    0.570   -0.021   -0.038
##     flow              -0.010    0.037   -0.256    0.798   -0.010   -0.017
##     turbid             0.017    0.038    0.441    0.659    0.017    0.030
##     temp              -0.063    0.033   -1.930    0.054   -0.063   -0.118
##     mysid_1           -0.040    0.036   -1.093    0.274   -0.040   -0.071
##   hcope_gr ~                                                             
##     chla_1             0.045    0.039    1.162    0.245    0.045    0.070
##     hcope_1           -0.363    0.039   -9.230    0.000   -0.363   -0.577
##     pcope_1           -0.053    0.034   -1.532    0.126   -0.053   -0.090
##     mysid_1            0.038    0.040    0.939    0.348    0.038    0.061
##     potam_1           -0.092    0.037   -2.500    0.012   -0.092   -0.150
##     flow              -0.088    0.040   -2.183    0.029   -0.088   -0.142
##     turbid            -0.040    0.041   -0.975    0.329   -0.040   -0.065
##     temp               0.036    0.035    1.025    0.305    0.036    0.062
##     estfish_bsmt_1     0.026    0.036    0.723    0.469    0.026    0.043
##     rotif_m_1          0.116    0.034    3.452    0.001    0.116    0.203
##   amphi_m_gr ~                                                           
##     chla_1            -0.080    0.064   -1.246    0.213   -0.080   -0.083
##     amphi_m_1         -0.315    0.061   -5.195    0.000   -0.315   -0.359
##     mysid_1            0.152    0.061    2.491    0.013    0.152    0.166
##     flow               0.003    0.063    0.051    0.959    0.003    0.003
##     turbid            -0.213    0.066   -3.226    0.001   -0.213   -0.230
##     temp              -0.162    0.058   -2.809    0.005   -0.162   -0.186
##     estfish_bsmt_1    -0.256    0.061   -4.174    0.000   -0.256   -0.285
##   rotif_m_gr ~                                                           
##     chla_1             0.013    0.113    0.119    0.905    0.013    0.008
##     rotif_m_1         -0.799    0.101   -7.939    0.000   -0.799   -0.511
##     flow               0.307    0.114    2.683    0.007    0.307    0.181
##     turbid            -0.337    0.114   -2.956    0.003   -0.337   -0.197
##     temp              -0.033    0.103   -0.326    0.745   -0.033   -0.021
##     estfish_bsmt_1    -0.264    0.104   -2.555    0.011   -0.264   -0.160
##   pcope_gr ~                                                             
##     hcope_1           -0.160    0.061   -2.618    0.009   -0.160   -0.169
##     pcope_1           -0.466    0.057   -8.213    0.000   -0.466   -0.526
##     mysid_1            0.143    0.064    2.247    0.025    0.143    0.154
##     potam_1            0.021    0.063    0.338    0.736    0.021    0.023
##     flow               0.125    0.063    1.977    0.048    0.125    0.134
##     turbid            -0.074    0.065   -1.138    0.255   -0.074   -0.079
##     temp               0.178    0.055    3.229    0.001    0.178    0.200
##     estfish_bsmt_1     0.004    0.058    0.076    0.939    0.004    0.005
##     rotif_m_1          0.114    0.056    2.046    0.041    0.114    0.132
##   mysid_gr ~                                                             
##     chla_1             0.270    0.084    3.217    0.001    0.270    0.206
##     hcope_1            0.078    0.082    0.951    0.342    0.078    0.061
##     pcope_1            0.126    0.074    1.717    0.086    0.126    0.106
##     amphi_m_1         -0.100    0.076   -1.318    0.188   -0.100   -0.084
##     mysid_1           -0.696    0.086   -8.140    0.000   -0.696   -0.556
##     flow              -0.209    0.081   -2.573    0.010   -0.209   -0.167
##     turbid             0.333    0.087    3.822    0.000    0.333    0.264
##     temp               0.118    0.075    1.565    0.118    0.118    0.099
##     estfish_bsmt_1     0.015    0.078    0.188    0.851    0.015    0.012
##   estfish_bsmt_gr ~                                                      
##     estfish_bsmt_1    -0.977    0.104   -9.417    0.000   -0.977   -0.589
##     hcope_1            0.098    0.107    0.919    0.358    0.098    0.057
##     pcope_1           -0.006    0.100   -0.063    0.950   -0.006   -0.004
##     amphi_m_1         -0.267    0.107   -2.485    0.013   -0.267   -0.164
##     rotif_m_1         -0.043    0.102   -0.419    0.675   -0.043   -0.027
##     mysid_1           -0.151    0.112   -1.350    0.177   -0.151   -0.089
##     flow              -0.211    0.108   -1.953    0.051   -0.211   -0.124
##     turbid             0.252    0.114    2.207    0.027    0.252    0.148
##     temp               0.067    0.097    0.689    0.491    0.067    0.041
## 
## Covariances:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##  .chla_gr ~~                                                            
##    .hcope_gr          0.057    0.016    3.579    0.000    0.057    0.260
##    .amphi_m_gr        0.000    0.025    0.008    0.994    0.000    0.001
##    .rotif_m_gr        0.080    0.045    1.771    0.077    0.080    0.126
##    .pcope_gr         -0.012    0.024   -0.483    0.629   -0.012   -0.034
##    .mysid_gr          0.076    0.033    2.312    0.021    0.076    0.165
##    .estfsh_bsmt_gr   -0.027    0.042   -0.630    0.529   -0.027   -0.044
##  .hcope_gr ~~                                                           
##    .amphi_m_gr       -0.055    0.027   -2.009    0.045   -0.055   -0.143
##    .rotif_m_gr       -0.043    0.049   -0.881    0.378   -0.043   -0.062
##    .pcope_gr          0.027    0.026    1.037    0.300    0.027    0.073
##    .mysid_gr          0.176    0.037    4.728    0.000    0.176    0.353
##    .estfsh_bsmt_gr   -0.116    0.047   -2.486    0.013   -0.116   -0.178
##  .amphi_m_gr ~~                                                         
##    .rotif_m_gr        0.214    0.081    2.632    0.008    0.214    0.188
##    .pcope_gr         -0.001    0.043   -0.018    0.986   -0.001   -0.001
##    .mysid_gr         -0.111    0.058   -1.910    0.056   -0.111   -0.136
##    .estfsh_bsmt_gr    0.046    0.075    0.605    0.545    0.046    0.043
##  .rotif_m_gr ~~                                                         
##    .pcope_gr         -0.103    0.077   -1.343    0.179   -0.103   -0.095
##    .mysid_gr         -0.148    0.104   -1.433    0.152   -0.148   -0.101
##    .estfsh_bsmt_gr    0.140    0.135    1.038    0.299    0.140    0.073
##  .pcope_gr ~~                                                           
##    .mysid_gr         -0.043    0.055   -0.771    0.440   -0.043   -0.054
##    .estfsh_bsmt_gr   -0.011    0.072   -0.150    0.881   -0.011   -0.011
##  .mysid_gr ~~                                                           
##    .estfsh_bsmt_gr   -0.068    0.097   -0.697    0.486   -0.068   -0.049
## 
## Variances:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##    .chla_gr           0.201    0.020   10.050    0.000    0.201    0.683
##    .hcope_gr          0.235    0.023   10.050    0.000    0.235    0.650
##    .amphi_m_gr        0.633    0.063   10.050    0.000    0.633    0.795
##    .rotif_m_gr        2.029    0.202   10.050    0.000    2.029    0.746
##    .pcope_gr          0.582    0.058   10.050    0.000    0.582    0.709
##    .mysid_gr          1.056    0.105   10.050    0.000    1.056    0.714
##    .estfsh_bsmt_gr    1.802    0.179   10.050    0.000    1.802    0.663
## 
## R-Square:
##                    Estimate
##     chla_gr           0.317
##     hcope_gr          0.350
##     amphi_m_gr        0.205
##     rotif_m_gr        0.254
##     pcope_gr          0.291
##     mysid_gr          0.286
##     estfsh_bsmt_gr    0.337
summary(modfitN, standardized=T, rsq=T)
## lavaan 0.6-10 ended normally after 59 iterations
## 
##   Estimator                                         ML
##   Optimization method                           NLMINB
##   Number of model parameters                        83
##                                                       
##                                                   Used       Total
##   Number of observations                           186         312
##                                                                   
## Model Test User Model:
##                                                       
##   Test statistic                                33.385
##   Degrees of freedom                                22
##   P-value (Chi-square)                           0.057
## 
## Parameter Estimates:
## 
##   Standard errors                             Standard
##   Information                                 Expected
##   Information saturated (h1) model          Structured
## 
## Regressions:
##                     Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##   chla_gr ~                                                              
##     chla_1            -0.408    0.047   -8.742    0.000   -0.408   -0.543
##     hcope_1            0.050    0.059    0.842    0.400    0.050    0.058
##     amphi_m_1          0.020    0.044    0.457    0.647    0.020    0.027
##     rotif_m_1          0.029    0.044    0.671    0.502    0.029    0.043
##     corbic_1          -0.018    0.044   -0.402    0.688   -0.018   -0.025
##     flow              -0.019    0.047   -0.391    0.696   -0.019   -0.027
##     turbid             0.030    0.044    0.675    0.500    0.030    0.044
##     temp               0.044    0.043    1.023    0.306    0.044    0.066
##   hcope_gr ~                                                             
##     chla_1             0.001    0.062    0.022    0.983    0.001    0.001
##     hcope_1           -0.820    0.099   -8.282    0.000   -0.820   -0.613
##     pcope_1           -0.096    0.061   -1.573    0.116   -0.096   -0.094
##     mysid_1            0.026    0.082    0.312    0.755    0.026    0.023
##     corbic_1           0.152    0.057    2.686    0.007    0.152    0.139
##     flow              -0.398    0.072   -5.514    0.000   -0.398   -0.371
##     turbid             0.146    0.069    2.108    0.035    0.146    0.138
##     temp               0.023    0.065    0.348    0.728    0.023    0.022
##     estfish_bsmt_1     0.005    0.065    0.073    0.942    0.005    0.005
##   amphi_m_gr ~                                                           
##     chla_1             0.064    0.072    0.891    0.373    0.064    0.058
##     amphi_m_1         -0.485    0.069   -6.991    0.000   -0.485   -0.440
##     flow               0.004    0.073    0.051    0.960    0.004    0.004
##     turbid            -0.062    0.068   -0.913    0.361   -0.062   -0.062
##     temp              -0.033    0.066   -0.498    0.619   -0.033   -0.033
##     estfish_bsmt_1    -0.060    0.067   -0.901    0.368   -0.060   -0.064
##   rotif_m_gr ~                                                           
##     chla_1            -0.222    0.135   -1.644    0.100   -0.222   -0.089
##     rotif_m_1         -1.501    0.127  -11.846    0.000   -1.501   -0.660
##     flow               0.861    0.142    6.070    0.000    0.861    0.379
##     turbid            -0.207    0.130   -1.596    0.111   -0.207   -0.092
##     temp              -0.027    0.127   -0.212    0.832   -0.027   -0.012
##     estfish_bsmt_1     0.031    0.128    0.244    0.807    0.031    0.015
##   pcope_gr ~                                                             
##     hcope_1           -0.071    0.168   -0.422    0.673   -0.071   -0.032
##     pcope_1           -1.006    0.106   -9.512    0.000   -1.006   -0.589
##     mysid_1            0.180    0.142    1.261    0.207    0.180    0.097
##     corbic_1           0.074    0.103    0.719    0.472    0.074    0.040
##     flow              -0.274    0.121   -2.268    0.023   -0.274   -0.153
##     turbid            -0.279    0.116   -2.401    0.016   -0.279   -0.157
##     temp               0.042    0.109    0.387    0.699    0.042    0.024
##     estfish_bsmt_1    -0.178    0.110   -1.616    0.106   -0.178   -0.107
##     chla_1             0.277    0.114    2.439    0.015    0.277    0.141
##   mysid_gr ~                                                             
##     hcope_1            0.038    0.302    0.126    0.900    0.038    0.009
##     pcope_1           -0.081    0.190   -0.425    0.671   -0.081   -0.025
##     mysid_1           -2.461    0.254   -9.693    0.000   -2.461   -0.710
##     amphi_m_1         -0.291    0.182   -1.597    0.110   -0.291   -0.079
##     flow              -1.170    0.216   -5.420    0.000   -1.170   -0.346
##     turbid             0.861    0.207    4.148    0.000    0.861    0.258
##     temp               0.157    0.191    0.818    0.413    0.157    0.048
##     estfish_bsmt_1     0.111    0.199    0.559    0.577    0.111    0.035
##   estfish_bsmt_gr ~                                                      
##     estfish_bsmt_1    -1.390    0.175   -7.925    0.000   -1.390   -0.567
##     hcope_1            0.189    0.274    0.690    0.490    0.189    0.057
##     pcope_1           -0.157    0.173   -0.910    0.363   -0.157   -0.063
##     amphi_m_1         -0.098    0.182   -0.537    0.591   -0.098   -0.034
##     rotif_m_1          0.168    0.178    0.943    0.346    0.168    0.064
##     mysid_1            0.322    0.230    1.402    0.161    0.322    0.119
##     flow              -0.500    0.193   -2.597    0.009   -0.500   -0.190
##     turbid             0.115    0.183    0.625    0.532    0.115    0.044
##     temp              -0.023    0.169   -0.136    0.892   -0.023   -0.009
## 
## Covariances:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##  .chla_gr ~~                                                            
##    .hcope_gr          0.113    0.037    3.043    0.002    0.113    0.229
##    .amphi_m_gr        0.047    0.038    1.256    0.209    0.047    0.092
##    .rotif_m_gr        0.104    0.072    1.433    0.152    0.104    0.106
##    .pcope_gr         -0.116    0.061   -1.904    0.057   -0.116   -0.141
##    .mysid_gr          0.089    0.108    0.826    0.409    0.089    0.061
##    .estfsh_bsmt_gr   -0.114    0.095   -1.201    0.230   -0.114   -0.088
##  .hcope_gr ~~                                                           
##    .amphi_m_gr        0.043    0.056    0.756    0.450    0.043    0.056
##    .rotif_m_gr       -0.438    0.112   -3.891    0.000   -0.438   -0.298
##    .pcope_gr          0.338    0.094    3.613    0.000    0.338    0.275
##    .mysid_gr          1.063    0.179    5.942    0.000    1.063    0.484
##    .estfsh_bsmt_gr   -0.159    0.142   -1.121    0.262   -0.159   -0.083
##  .amphi_m_gr ~~                                                         
##    .rotif_m_gr        0.188    0.113    1.662    0.096    0.188    0.123
##    .pcope_gr         -0.340    0.097   -3.489    0.000   -0.340   -0.265
##    .mysid_gr          0.154    0.168    0.918    0.359    0.154    0.067
##    .estfsh_bsmt_gr   -0.204    0.148   -1.374    0.169   -0.204   -0.101
##  .rotif_m_gr ~~                                                         
##    .pcope_gr         -0.344    0.182   -1.894    0.058   -0.344   -0.140
##    .mysid_gr         -1.034    0.330   -3.135    0.002   -1.034   -0.236
##    .estfsh_bsmt_gr   -0.279    0.283   -0.985    0.325   -0.279   -0.072
##  .pcope_gr ~~                                                           
##    .mysid_gr          0.905    0.277    3.268    0.001    0.905    0.247
##    .estfsh_bsmt_gr    0.439    0.238    1.842    0.065    0.439    0.136
##  .mysid_gr ~~                                                           
##    .estfsh_bsmt_gr   -0.060    0.421   -0.143    0.887   -0.060   -0.010
## 
## Variances:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##    .chla_gr           0.329    0.034    9.644    0.000    0.329    0.697
##    .hcope_gr          0.737    0.076    9.644    0.000    0.737    0.643
##    .amphi_m_gr        0.801    0.083    9.644    0.000    0.801    0.783
##    .rotif_m_gr        2.933    0.304    9.644    0.000    2.933    0.568
##    .pcope_gr          2.055    0.213    9.644    0.000    2.055    0.638
##    .mysid_gr          6.540    0.678    9.644    0.000    6.540    0.575
##    .estfsh_bsmt_gr    5.044    0.523    9.644    0.000    5.044    0.728
## 
## R-Square:
##                    Estimate
##     chla_gr           0.303
##     hcope_gr          0.357
##     amphi_m_gr        0.217
##     rotif_m_gr        0.432
##     pcope_gr          0.362
##     mysid_gr          0.425
##     estfsh_bsmt_gr    0.272
summary(modfitS, standardized=T, rsq=T)
## lavaan 0.6-10 ended normally after 41 iterations
## 
##   Estimator                                         ML
##   Optimization method                           NLMINB
##   Number of model parameters                        81
##                                                       
##                                                   Used       Total
##   Number of observations                           192         312
##                                                                   
## Model Test User Model:
##                                                       
##   Test statistic                                24.127
##   Degrees of freedom                                24
##   P-value (Chi-square)                           0.454
## 
## Parameter Estimates:
## 
##   Standard errors                             Standard
##   Information                                 Expected
##   Information saturated (h1) model          Structured
## 
## Regressions:
##                     Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##   chla_gr ~                                                              
##     chla_1            -0.493    0.050   -9.865    0.000   -0.493   -0.607
##     hcope_1            0.054    0.047    1.156    0.248    0.054    0.067
##     clad_1             0.141    0.044    3.208    0.001    0.141    0.188
##     rotif_m_1         -0.054    0.045   -1.195    0.232   -0.054   -0.068
##     corbic_1          -0.011    0.045   -0.253    0.800   -0.011   -0.014
##     flow              -0.087    0.051   -1.702    0.089   -0.087   -0.105
##     turbid            -0.005    0.046   -0.116    0.908   -0.005   -0.007
##     temp               0.022    0.045    0.487    0.626    0.022    0.029
##   hcope_gr ~                                                             
##     chla_1             0.148    0.058    2.538    0.011    0.148    0.158
##     hcope_1           -0.457    0.057   -8.055    0.000   -0.457   -0.493
##     pcope_1            0.009    0.054    0.171    0.864    0.009    0.010
##     corbic_1           0.107    0.055    1.960    0.050    0.107    0.117
##     flow              -0.119    0.062   -1.923    0.055   -0.119   -0.125
##     turbid            -0.087    0.057   -1.519    0.129   -0.087   -0.098
##     temp               0.059    0.057    1.034    0.301    0.059    0.066
##     estfish_bsmt_1    -0.132    0.056   -2.372    0.018   -0.132   -0.149
##   clad_gr ~                                                              
##     chla_1             0.273    0.092    2.962    0.003    0.273    0.199
##     clad_1            -0.604    0.085   -7.136    0.000   -0.604   -0.475
##     pcope_1            0.034    0.084    0.408    0.683    0.034    0.026
##     flow               0.238    0.092    2.587    0.010    0.238    0.171
##     turbid            -0.080    0.086   -0.926    0.355   -0.080   -0.061
##     temp               0.033    0.086    0.383    0.701    0.033    0.025
##     estfish_bsmt_1    -0.124    0.083   -1.491    0.136   -0.124   -0.095
##   amphi_m_gr ~                                                           
##     chla_1            -0.042    0.095   -0.440    0.660   -0.042   -0.025
##     amphi_m_1         -0.885    0.089   -9.914    0.000   -0.885   -0.594
##     flow              -0.075    0.100   -0.751    0.453   -0.075   -0.045
##     turbid             0.198    0.096    2.069    0.039    0.198    0.127
##     temp               0.082    0.093    0.883    0.377    0.082    0.053
##     estfish_bsmt_1     0.061    0.094    0.642    0.521    0.061    0.039
##   rotif_m_gr ~                                                           
##     chla_1            -0.064    0.101   -0.632    0.527   -0.064   -0.037
##     rotif_m_1         -0.986    0.095  -10.400    0.000   -0.986   -0.579
##     flow               0.367    0.104    3.524    0.000    0.367    0.209
##     turbid            -0.101    0.097   -1.033    0.302   -0.101   -0.061
##     temp              -0.032    0.097   -0.332    0.740   -0.032   -0.020
##     estfish_bsmt_1     0.124    0.096    1.288    0.198    0.124    0.075
##   pcope_gr ~                                                             
##     chla_1             0.377    0.101    3.749    0.000    0.377    0.232
##     hcope_1           -0.121    0.100   -1.208    0.227   -0.121   -0.075
##     clad_1             0.102    0.096    1.057    0.291    0.102    0.068
##     pcope_1           -0.762    0.097   -7.857    0.000   -0.762   -0.491
##     corbic_1           0.046    0.094    0.488    0.625    0.046    0.029
##     flow               0.003    0.106    0.031    0.975    0.003    0.002
##     turbid            -0.100    0.097   -1.027    0.305   -0.100   -0.064
##     temp               0.001    0.096    0.013    0.990    0.001    0.001
##     estfish_bsmt_1    -0.060    0.097   -0.616    0.538   -0.060   -0.039
##   estfish_bsmt_gr ~                                                      
##     estfish_bsmt_1    -1.451    0.174   -8.335    0.000   -1.451   -0.524
##     hcope_1           -0.007    0.177   -0.039    0.969   -0.007   -0.002
##     pcope_1           -0.207    0.173   -1.200    0.230   -0.207   -0.074
##     amphi_m_1          0.242    0.159    1.519    0.129    0.242    0.091
##     rotif_m_1         -0.035    0.168   -0.208    0.835   -0.035   -0.012
##     clad_1             0.277    0.168    1.650    0.099    0.277    0.102
##     flow              -0.156    0.191   -0.818    0.413   -0.156   -0.053
##     turbid             0.494    0.177    2.793    0.005    0.494    0.177
##     temp              -0.025    0.172   -0.146    0.884   -0.025   -0.009
## 
## Covariances:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##  .chla_gr ~~                                                            
##    .hcope_gr          0.124    0.036    3.429    0.001    0.124    0.255
##    .clad_gr           0.200    0.055    3.663    0.000    0.200    0.274
##    .amphi_m_gr        0.018    0.058    0.315    0.752    0.018    0.023
##    .rotif_m_gr        0.184    0.062    2.980    0.003    0.184    0.220
##    .pcope_gr         -0.006    0.059   -0.095    0.924   -0.006   -0.007
##    .estfsh_bsmt_gr   -0.082    0.106   -0.777    0.437   -0.082   -0.056
##  .hcope_gr ~~                                                           
##    .clad_gr           0.199    0.066    3.005    0.003    0.199    0.222
##    .amphi_m_gr        0.104    0.071    1.455    0.146    0.104    0.106
##    .rotif_m_gr       -0.211    0.075   -2.804    0.005   -0.211   -0.207
##    .pcope_gr          0.092    0.072    1.268    0.205    0.092    0.092
##    .estfsh_bsmt_gr   -0.302    0.131   -2.298    0.022   -0.302   -0.168
##  .clad_gr ~~                                                            
##    .amphi_m_gr        0.086    0.107    0.808    0.419    0.086    0.058
##    .rotif_m_gr        0.219    0.113    1.946    0.052    0.219    0.142
##    .pcope_gr          0.078    0.109    0.719    0.472    0.078    0.052
##    .estfsh_bsmt_gr   -0.217    0.196   -1.107    0.268   -0.217   -0.080
##  .amphi_m_gr ~~                                                         
##    .rotif_m_gr       -0.077    0.122   -0.628    0.530   -0.077   -0.045
##    .pcope_gr         -0.154    0.119   -1.288    0.198   -0.154   -0.093
##    .estfsh_bsmt_gr   -0.659    0.219   -3.006    0.003   -0.659   -0.222
##  .rotif_m_gr ~~                                                         
##    .pcope_gr          0.295    0.126    2.342    0.019    0.295    0.171
##    .estfsh_bsmt_gr    0.298    0.224    1.329    0.184    0.298    0.096
##  .pcope_gr ~~                                                           
##    .estfsh_bsmt_gr    0.738    0.224    3.295    0.001    0.738    0.245
## 
## Variances:
##                    Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
##    .chla_gr           0.394    0.040    9.798    0.000    0.394    0.653
##    .hcope_gr          0.593    0.061    9.798    0.000    0.593    0.737
##    .clad_gr           1.349    0.138    9.798    0.000    1.349    0.783
##    .amphi_m_gr        1.621    0.165    9.798    0.000    1.621    0.658
##    .rotif_m_gr        1.766    0.180    9.798    0.000    1.766    0.642
##    .pcope_gr          1.676    0.171    9.798    0.000    1.676    0.694
##    .estfsh_bsmt_gr    5.423    0.553    9.798    0.000    5.423    0.692
## 
## R-Square:
##                    Estimate
##     chla_gr           0.347
##     hcope_gr          0.263
##     clad_gr           0.217
##     amphi_m_gr        0.342
##     rotif_m_gr        0.358
##     pcope_gr          0.306
##     estfsh_bsmt_gr    0.308
#modificationindices(modfitW, sort=T, maximum.number=20)
#residuals(modfitW)

labelsfarwest=createLabels(modfitFW, cnameslag)
labelswest=createLabels(modfitW, cnameslag)
labelsnorth=createLabels(modfitN, cnameslag)
labelssouth=createLabels(modfitS, cnameslag)

#FAR WEST
zoop_plot_far_west <- createGraph(fit=modfitFW, 
                                  reference_df=cnameslag, 
                                  model_type="monthly_zoop",
                                  region="Far West",
                                  title="Far West",
                                  manual_port_settings=TRUE)
zoop_plot_far_west
#WEST
zoop_plot_west <- createGraph(fit=modfitW, 
                              reference_df=cnameslag, 
                              model_type="monthly_zoop",
                              region="West",
                              title="West",
                              manual_port_settings=TRUE)
zoop_plot_west
#NORTH
zoop_plot_north <- createGraph(fit=modfitN, 
                               reference_df=cnameslag, 
                               model_type="monthly_zoop",
                               region="North",
                               title="North",
                               manual_port_settings=TRUE)
zoop_plot_north
#SOUTH
zoop_plot_south <- createGraph(fit=modfitS, 
                               reference_df=cnameslag, 
                               model_type="monthly_zoop",
                               region="South",
                               title="South",
                               manual_port_settings=TRUE)
zoop_plot_south